Meltdown Minder Knowledge Base

54 papers in the vault

54 papers • 3 pending • Tier Tier 1: 17 • Tier Tier 2: 27 • Tier Tier 3: 10

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Min n: 0

Tier 3 unknown

Meltdown Minder — Current Architecture & Capabilities

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — internal project documentation.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — internal project documentation.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — internal project documentation.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
N/A — internal project documentation.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — internal project documentation.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — internal project documentation.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown n=909

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=909. Population: ASD. Setting: inpatient. Setting: clinical.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — reference/resource document.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Clinical setting. Laboratory. During sleep. Free-living. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
ABC, VAS, Clinician-rated, Direct observation, Self-report, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — reference/resource document.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=909.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown

Empatica E4 Research Resources

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — reference/resource document.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — reference/resource document.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — reference/resource document.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — reference/resource document.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown

WHOOP Developer Blog & API Docs

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — reference/resource document.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — reference/resource document.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory. During sleep.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — reference/resource document.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — reference/resource document.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown n=65

The Crown Jewel — MVP Roadmap

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=65. Population: ASD. Setting: clinical.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — internal project documentation.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Clinical setting. Laboratory. During sleep. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — internal project documentation.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=65.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

AffectiveROAD

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics and recruitment details.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=62

CLAS — Cognitive Load, Affect, and Stress

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=62.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=62.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

Regulation of Brain Cognitive States Through Sensory Stimulation with Wearable Monitoring

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
See dataset documentation for recording conditions and protocols.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
See dataset documentation for label definitions and annotation procedures.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

CogWear — Cognitive Effort Detection with Consumer Wearables

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
See dataset documentation for recording conditions and protocols.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
See dataset documentation for label definitions and annotation procedures.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=142

DAPPER — Dataset for Affective Processing in Real-World Environments

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=142.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-report, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=142.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=32

DEAP — Database for Emotion Analysis using Physiological Signals

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=32.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-report, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=32.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

FEEL Benchmark

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics and recruitment details.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=20

Goodwin — Autism Inpatient Collection (AIC)

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=20. Population: ASD. Setting: inpatient.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
VAS, Direct observation, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=20.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=70

Imbiriba — JAMA Network Open 2023 (AIC Extension)

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=70. Population: ASD. Setting: inpatient.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=70.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=30

K-EmoCon

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=30.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-report, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=30.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

Nurse Stress Dataset (Hosseini 2022)

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Population: ASD.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-report, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=3

REACT — Real-time Early Agitation Capture Technology (Vanderbilt)

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=3. Population: ASD.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=3.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

ScientISST MOVE — Naturalistic Activity Monitoring

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
See dataset documentation for recording conditions and protocols.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
See dataset documentation for label definitions and annotation procedures.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

Neurophysiological Dataset of Stress Resilience During Human-Computer Interaction

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
See dataset documentation for recording conditions and protocols.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
See dataset documentation for label definitions and annotation procedures.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=25

SWELL-KW

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=25.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=25.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=212

TILES-2018

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=212.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory. Free-living. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-report, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=212.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=15

WESAD — Wearable Stress and Affect Detection

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=15.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=15.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

Multimodal Dataset for Investigating Working Memory in Presence of Music

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
See dataset documentation for participant demographics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable sensors (see dataset documentation for device specifications, sampling rates, and placement).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
See dataset documentation for recording conditions and protocols.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
See dataset documentation for label definitions and annotation procedures.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See dataset documentation for preprocessing and quality control details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
See dataset documentation for completeness and exclusion details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown n=335

Meltdown and Tantrum Categorization

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=335. Population: ASD. Setting: clinical.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — internal project documentation.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Clinical setting. Laboratory. During sleep.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — internal project documentation.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=335.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=1

Aljassmi 2025 — Longitudinal Case Study on Detecting Emotional Dysregulation in a Child with ASD Using Wearable Sensors

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=1; 10-year-old child with ASD; convenience sample (single working-parent family).
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Empatica EmbracePlus; EDA, HR, accelerometry; 3 months continuous monitoring.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Home, naturalistic, free-living; caregiver-installed video cameras for retrospective event validation.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Caregiver-confirmed heightened-arousal episodes via retrospective review of home video footage whenever wearable flagged abnormal physiology.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Unsupervised anomaly detection; rolling-window + peak-detection feature extraction; video-based retrospective confirmation.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=1; single-subject case study, work-in-progress.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported; case study.
Tier 2 unknown

Ferina 2025 — Approaches for Predicting Challenging Behaviors in ASD: A Narrative Review

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Systematic review — no original subject recruitment. Literature search across academic databases.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — review article. Synthesizes findings from published studies using various sensor modalities.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — review article. Draws from studies across clinical, home, lab, and naturalistic settings.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
N/A — review article. Outcome measures vary by included study; typically clinician-rated scales or diagnostic criteria.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — review article. Quality assessment of included studies per PRISMA or similar guidelines.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — review article. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=70

Goodwin 2019 — Predicting Aggression to Others in Youth with ASD Using a Wearable Biosensor

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=70. Age range: 6-17 yr. Population: ASD. Setting: inpatient.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
EDA, ACC, TEMP. Wearable/wrist-worn device.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Naturalistic setting. Inpatient unit. Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
VAS, Direct observation, Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See paper for preprocessing and validation details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=70.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=70

Imbiriba 2023 — Wearable Biosensing to Predict Imminent Aggressive Behavior in Psychiatric Inpatient Youths With Autism

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=70. Age range: 5-19 yr. Population: ASD. Setting: inpatient.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Empatica E4. Wearable/wrist-worn device.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Inpatient unit. Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See paper for preprocessing and validation details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=70.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

Jerritta 2026 — RQA-Based Identification of Emotions from ECG Signals for Emotion Regulation in Children with ASD

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Children with ASD. See paper for n, inclusion criteria, and demographics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
ECG signals. See paper for device, sampling rate, and placement.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Controlled emotion elicitation protocol. See paper for task design.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Emotional state labels (likely self-report or behavioral observation). See paper.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Recurrence Quantification Analysis (RQA) feature extraction. Classification metrics reported in paper.
Missingness
n=X subjects — do all have complete data? Describe pattern.
Not reported in abstract; see paper.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported.
Tier 1 unknown n=9

Kartha 2026 — Prediction of Challenging Behaviors in Profound Autism: Classroom Setting Wearable Sensors

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=9 children/young adults (ages 10-21) with profound autism in a special-education classroom.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Multimodal wearable; accelerometry, EDA, skin temperature.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Real-world special-education classroom. Naturalistic standard sessions.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Challenging-behavior episode labels (SIB, aggression, elopement, pica). See paper for coding procedure.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Foundation-model fine-tuning; AUC-ROC 0.78 evaluation.
Missingness
n=X subjects — do all have complete data? Describe pattern.
~110.7 h labeled data across 9 subjects. Details in paper.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported in abstract; see paper.
Tier 1 unknown n=3

Khan 2024 — REACT: Real-time Early Agitation Capture Technology

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=3. Age range: 6-9 yr. Population: ASD.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
EDA, ACC. Wearable/wrist-worn device.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Naturalistic setting. Laboratory. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
See paper for preprocessing and validation details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=3.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown

Khan 2025 — A Universal Web-Based Tool for Multimodal Data Synchronization and Labeling

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — tool development paper. No original subject recruitment.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — tool designed for multimodal data (video + physiological signals).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — tool methodology paper.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Tool provides manual labeling interface for behavioral annotations.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Tool validation described in paper.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — no primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=9

Kim 2026 — Feasibility of Forecasting Self-Injurious Behavior in Autistic Youth Using Wearable Sensors

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=9 autistic youth; secondary analysis of previously collected dataset.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Wearable accelerometers + physiological sensors (heart rate, skin conductance).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
From prior source study — see source dataset publication for setting details.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
SIB event labels from prior dataset (see source publication).
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Leave-One-Subject-Out cross-validation; AUPRC metrics; 4 models x 5 horizons x 3 feature sets.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=9; per-subject completeness from source dataset.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported in abstract; see paper.
Tier 2 unknown

Kumar 2026 — Stereotypic Repetitive Behavior Monitoring Using Human Body Communication

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Not reported in abstract; see paper. IEEE Sensors Journal — likely controlled evaluation.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Human Body Communication (HBC) — body-as-waveguide signal transmission. No external wearable sensor required beyond body-worn electrodes.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Likely controlled/laboratory setting (see paper).
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Stereotypic repetitive behavior labels — see paper for annotation method.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Detection accuracy for common SRB topographies. See paper for metrics.
Missingness
n=X subjects — do all have complete data? Describe pattern.
Not reported in abstract; see paper.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported.
Tier 2 unknown n=5

Medina 2025 — Wearable HRV Stress Detection and Intervention for Sensory Overload in Children with Autism in the Philippines

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=5 high-functioning children with ASD; device validation study.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
DFRobot Gravity PPG HR sensor; Arduino ESP32; wrist and finger placements.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Controlled physical activity (before/after protocol); intended for educational and everyday settings.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
HR/HRV stress scores; comparative validation against commercial wearable band.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Pearson correlation (r=0.97) and mean difference (2.00 BPM) vs. reference device.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=5; see paper for completeness details.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported.
Tier 3 unknown n=55

Patel 2026 — Caregiver Needs and Technology Acceptability for Behavioral-Crisis Support in Children With Neurodevelopmental or Behavioral Conditions

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Convenience sample of caregivers (n=55 interim, target 75) of children aged 5-17 with neurodevelopmental or behavioral conditions; single-center; prior crisis experience not required.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Online REDCap survey, 24-item instrument.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Cross-sectional survey; open recruitment via flyers, email, and in-person clinic invitations.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Caregiver self-report; no clinical gold standard.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Estimation-first analyses; Wilson 95% CIs; medians with IQRs; pre-specified bivariate ordinal tests (Kendall's tau-b, Jonckheere-Terpstra, Friedman).
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=55 interim; response rate undetermined due to open-ended recruitment; hypothesis-generating.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not reported; interim analysis.
Tier 2 unknown

Pergantis 2025 — Assistive and Emerging Technologies to Detect and Reduce Neurophysiological Stress and Anxiety in Children and Adolescents with Autism: A Systematic Review

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Systematic review — no original subject recruitment. PRISMA-guided literature search across academic databases.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — review article. Synthesizes findings from studies using various assistive/emerging technologies.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — review article. Draws from studies across clinical, home, school, and lab settings.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
N/A — review article. Outcome measures vary by included study.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
PRISMA quality assessment of included studies.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — review article. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=70

Potter 2026 — Temporal Point Process Modeling of Aggressive Behavior Onset in Autistic Youth

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=70. Youth with ASD (ages 6-20) from inpatient psychiatric units. Subset of AIC (Autism Inpatient Collection).
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Empatica E4 wristband. EDA (4Hz), PPG (64Hz), ACC (32Hz), TEMP (4Hz). Continuous monitoring for up to 14 days.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Inpatient psychiatric unit. Naturalistic observation during daily activities. No structured tasks. Clinical staff logged aggression events via OAS-M.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
OAS-M (Overt Aggression Scale — Modified). Events coded by clinical staff via direct observation and chart review. Inter-rater reliability: κ > 0.80.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Temporal point process modeling. Event times validated against clinical logs. EDA signal quality assessed via standard deviation thresholding.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=70 enrolled. 62 with complete data (8 excluded: device failure, early discharge, or insufficient event data). Missingness correlated with high-agitation periods.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Missing not at random
Tier 2 unknown

Romani 2026 — Using Wearable Technology to Predict Severe Behavior Problems: A Systematic Review

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Systematic review — no original subject recruitment. Literature search across academic databases.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — review article. Synthesizes findings from published studies using various sensor modalities.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — review article. Draws from studies across clinical, home, lab, and naturalistic settings.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
N/A — review article. Outcome measures vary by included study; typically clinician-rated scales or diagnostic criteria.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — review article. Quality assessment of included studies per PRISMA or similar guidelines.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — review article. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=15

Schmidt 2018 — WESAD: Wearable Stress and Affect Detection

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=15. Healthy adults (mean age 27.5). 3 conditions: baseline, amusement, stress. Recruited from university community.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Empatica E4 wristband (EDA, BVP, ACC, TEMP) + RespiBAN chest strap (ECG, EMG, RESP, ACC). Both devices worn simultaneously.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory setting. Structured protocol: 20-min baseline, 7-min amusement video, 10-min Trier Social Stress Test, 10-min recovery. Each session ~2 hours.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-report (SAM, PANAS, SSSQ). Physiological state defined by protocol phase (baseline vs stress vs amusement). No clinician-rated labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Manual artifact inspection. EDA artifacts removed via visual inspection. ECG: Pan-Tompkins for R-peak detection. Accelerometer non-wear detected via zero-variance.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=15 enrolled. All 15 completed full protocol. No missing data reported. Complete data for all participants across all sensors.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown n=1

Singh 2026 — FEEL: Quantifying Heterogeneity in Physiological Signals for Generalizable Emotion Recognition

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=1,021. Pooled from 13 public datasets (WESAD, DEAP, DAPPER, etc.). Diverse demographics. No original recruitment.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
PPG (from Empatica E4, Polar H7, and other wearables). Sampling rates vary by source dataset (64-256Hz).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Pooled analysis of 13 existing datasets. Original acquisition contexts vary: lab, controlled, and naturalistic settings.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Self-reported emotion labels (valence, arousal, dominance per SAM). Labels normalized across datasets via harmonization procedure.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Signal quality filtering: PPG signals with SNR < 3dB excluded. Inter-beat interval outliers removed via MAD-based thresholding. Harmonization pipeline validated on held-out dataset.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=1,021 pooled from 13 datasets. Each dataset had independent exclusion criteria. Full details in source dataset publications.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Missing
Tier 1 unknown n=45

Stewart 2026 — Comparative Evaluation of Wearable Sensor Form Factors in ASD Youth

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=45. Children with ASD (ages 5-12). Recruited from outpatient clinics and community organizations. Parent-reported diagnosis confirmed via ADOS.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Four devices compared: Empatica E4 (wrist), Polar H10 (chest), Actigraph wGT3X-BT (hip), and custom BVP sensor (finger). Simultaneous wear for 24h.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Home environment. Free-living conditions. Parents instructed to maintain normal daily routines. Devices worn for 24 consecutive hours.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Parent-reported comfort/skin irritation logs. Device wear-time validated via accelerometer non-wear detection. No clinical outcome events.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Cross-device comparison of signal quality metrics. Wear-time validation via multiple sensors. Skin irritation assessed via parent diary.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=45 enrolled. 42 completed full protocol (3 excluded: 1 device intolerance, 2 data loss due to Bluetooth disconnection). 93% complete wear-time data.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Missing
Tier 1 Pending semantic_scholar 2025

Integrating Artificial Intelligence, Internet of Things, and Sensor-Based Technologies: A Systematic Review of Methodologies in Autism Spectrum Disorder Detection (2025)

Authors: Georgios Bouchouras, Konstantinos Kotis

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Systematic review — no original subject recruitment. Searched IEEE, PubMed, Scopus, Web of Science for studies on AI/IoT for ASD detection.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — systematic review. Reviewed studies using wearable sensors, EEG, eye-tracking, and video-based systems for ASD detection.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — systematic review. Pulls from published studies across clinical, home, and lab settings.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
N/A — systematic review. Outcomes based on ADOS, ADI-R, DSM-5 criteria for ASD diagnosis as reported in included studies.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
PRISMA guidelines followed. Dual screening, quality assessment of included studies via QUADAS-2 or similar tool.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — systematic review. No primary data collection; reports on completeness of search and screening according to PRISMA.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 Pending crossref 2027

MXene-based biosensors for biomedical diagnostics: From molecular recognition to wearable systems (2027)

Authors: Shamsheeth Khan Sardar Khan, Govindaraj Sabarees

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — review article. No human subjects. Covers MXene-based biosensor platforms for biomedical diagnostics.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — review article. Discusses electrochemical, optical, and wearable MXene sensor platforms for biomarker detection (glucose, cortisol, cytokines).
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
N/A — review article. Surveys in vitro, ex vivo, and in vivo sensor validation studies from published literature.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
N/A — review article. No outcome events. Discusses sensor sensitivity, LOD, and selectivity benchmarks from published studies.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — review article. Compares sensor performance metrics (sensitivity, detection range, response time) across published studies.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — review article. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 Pending semantic_scholar n=70 2025

Temporal point process modeling of aggressive behavior onset in psychiatric inpatient youths with autism (2025)

Authors: Michael Potter, Michael Everett, Ashutosh Singh et al.

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=70. Youth with ASD (ages 6-20) from inpatient psychiatric units. 75% male, 85% minimally verbal. Recruited from 4 sites as part of AIC (Autism Inpatient Collection).
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Empatica E4 wristband. Sensors: EDA (4Hz), PPG (64Hz), ACC (32Hz), TEMP (4Hz). Data streamed via Bluetooth to study tablet.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Inpatient psychiatric unit. Continuous monitoring during naturalistic daily activities (meals, therapy, recreation, sleep). No structured tasks. Duration: up to 14 days per participant.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Aggression events defined per OAS-M (Overt Aggression Scale — Modified). Events coded by trained clinical staff via direct observation and chart review. Inter-rater reliability: κ > 0.80.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Manual artifact rejection by trained research assistants. EDA artifacts identified via sudden drops > 5μS. ACC non-wear detected via zero-variance windows. Cross-modal validation between EDA and HRV peaks.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=70 enrolled. 62 completed full protocol (8 excluded: 4 device failure, 2 early discharge, 2 withdrew). Missing data: 11% of monitoring hours lost due to device disconnection or signal quality. Missingness correlated with high-agitation periods (MNAR).
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Missing not at random
Tier 1 unknown

Autonomic Dysregulation in ASD

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Population: ASD.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Synthesized from published literature. See referenced studies for device specifications.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Synthesized from published literature. See referenced studies for validation procedures.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — physiology summary. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown

Hot-blooded vs Cold-blooded Aggression Physiology

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Setting: clinical.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Synthesized from published literature. See referenced studies for device specifications.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Clinical setting. Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Synthesized from published literature. See referenced studies for validation procedures.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — physiology summary. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown

Meltdown Physiological Signature

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — physiology summary document. Synthesizes findings from multiple studies.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Synthesized from published literature. See referenced studies for device specifications.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Synthesized from published literature. See referenced studies for validation procedures.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — physiology summary. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown n=1

Rumble Detection Physiology

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
n=1.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Synthesized from published literature. See referenced studies for device specifications.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Synthesized from published literature. See referenced studies for validation procedures.
Missingness
n=X subjects — do all have complete data? Describe pattern.
n=1.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 1 unknown

Tantrum vs Meltdown Physiology

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Setting: clinical.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
Synthesized from published literature. See referenced studies for device specifications.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Clinical setting. Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
Synthesized from published literature. See referenced studies for validation procedures.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — physiology summary. No primary data collection.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown

REACT — Real-time Early Agitation Capture Technology

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
Population: ASD.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — reference/resource document.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory. Real-world.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — reference/resource document.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — reference/resource document.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

FEEL Benchmark Code

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — code repository. See linked dataset documentation.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — code repository. See linked dataset documentation.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — code repository. See linked dataset and paper for details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — code repository. See linked dataset documentation.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 2 unknown

WESAD Baseline Implementations

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — code repository. See linked dataset documentation.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — code repository. See linked dataset documentation.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — code repository. See linked dataset and paper for details.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — code repository. See linked dataset documentation.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed
Tier 3 unknown

WHOOP 5.0/MG Protocol Schema — NOOP-Audited

Authors:

DOI:

Subject Selection
How were subjects selected? Inclusion/exclusion criteria, sampling strategy, n=? Power analysis?
N/A — reference/resource document.
Data Acquisition
How was data physically acquired? Device model (E4, Empatica, WHOOP, Polar), sampling rate, placement, firmware.
N/A — reference/resource document.
Acquisition Context
From whom, what were they doing during recording? Clinic, home, school, sleep-only, free-living, task-based?
Laboratory.
Gold Standard Labels
How were outcome events defined? Clinician-validated scale (ABCD, ABC, CAAS, VAS), event logs, direct observation?
Event labels.
Data Validation
How were data fields validated? Artifact rejection, signal quality indices, cross-modal checks, QC pipeline?
N/A — reference/resource document.
Missingness
n=X subjects — do all have complete data? Describe pattern.
N/A — reference/resource document.
Missing Type
Missing, Missing at random, Missing completely at random, Missing not at random
Not assessed

Meltdown Minder Knowledge Base

Meltdown Minder — Current Architecture & Capabilities

Empatica E4 Research Resources

WHOOP Developer Blog & API Docs

The Crown Jewel — MVP Roadmap

AffectiveROAD

CLAS — Cognitive Load, Affect, and Stress

Regulation of Brain Cognitive States Through Sensory Stimulation with Wearable Monitoring

CogWear — Cognitive Effort Detection with Consumer Wearables

DAPPER — Dataset for Affective Processing in Real-World Environments

DEAP — Database for Emotion Analysis using Physiological Signals

FEEL Benchmark

Goodwin — Autism Inpatient Collection (AIC)

Imbiriba — JAMA Network Open 2023 (AIC Extension)

K-EmoCon

Nurse Stress Dataset (Hosseini 2022)

REACT — Real-time Early Agitation Capture Technology (Vanderbilt)

ScientISST MOVE — Naturalistic Activity Monitoring

Neurophysiological Dataset of Stress Resilience During Human-Computer Interaction

SWELL-KW

TILES-2018

WESAD — Wearable Stress and Affect Detection

Multimodal Dataset for Investigating Working Memory in Presence of Music

Meltdown and Tantrum Categorization

Aljassmi 2025 — Longitudinal Case Study on Detecting Emotional Dysregulation in a Child with ASD Using Wearable Sensors

Ferina 2025 — Approaches for Predicting Challenging Behaviors in ASD: A Narrative Review

Goodwin 2019 — Predicting Aggression to Others in Youth with ASD Using a Wearable Biosensor

Imbiriba 2023 — Wearable Biosensing to Predict Imminent Aggressive Behavior in Psychiatric Inpatient Youths With Autism

Jerritta 2026 — RQA-Based Identification of Emotions from ECG Signals for Emotion Regulation in Children with ASD

Kartha 2026 — Prediction of Challenging Behaviors in Profound Autism: Classroom Setting Wearable Sensors

Khan 2024 — REACT: Real-time Early Agitation Capture Technology

Khan 2025 — A Universal Web-Based Tool for Multimodal Data Synchronization and Labeling

Kim 2026 — Feasibility of Forecasting Self-Injurious Behavior in Autistic Youth Using Wearable Sensors

Kumar 2026 — Stereotypic Repetitive Behavior Monitoring Using Human Body Communication

Medina 2025 — Wearable HRV Stress Detection and Intervention for Sensory Overload in Children with Autism in the Philippines

Patel 2026 — Caregiver Needs and Technology Acceptability for Behavioral-Crisis Support in Children With Neurodevelopmental or Behavioral Conditions

Pergantis 2025 — Assistive and Emerging Technologies to Detect and Reduce Neurophysiological Stress and Anxiety in Children and Adolescents with Autism: A Systematic Review

Potter 2026 — Temporal Point Process Modeling of Aggressive Behavior Onset in Autistic Youth

Romani 2026 — Using Wearable Technology to Predict Severe Behavior Problems: A Systematic Review

Schmidt 2018 — WESAD: Wearable Stress and Affect Detection

Singh 2026 — FEEL: Quantifying Heterogeneity in Physiological Signals for Generalizable Emotion Recognition

Stewart 2026 — Comparative Evaluation of Wearable Sensor Form Factors in ASD Youth

Integrating Artificial Intelligence, Internet of Things, and Sensor-Based Technologies: A Systematic Review of Methodologies in Autism Spectrum Disorder Detection (2025)

MXene-based biosensors for biomedical diagnostics: From molecular recognition to wearable systems (2027)

Temporal point process modeling of aggressive behavior onset in psychiatric inpatient youths with autism (2025)

Autonomic Dysregulation in ASD

Hot-blooded vs Cold-blooded Aggression Physiology

Meltdown Physiological Signature

Rumble Detection Physiology

Tantrum vs Meltdown Physiology

REACT — Real-time Early Agitation Capture Technology

FEEL Benchmark Code

WESAD Baseline Implementations

WHOOP 5.0/MG Protocol Schema — NOOP-Audited