hr physiological data empatica e4 (Empatica Inc)
90
Structured Review
Empatica Inc
hr physiological data empatica e4
Hr Physiological Data Empatica E4, supplied by Empatica Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/physiological+data+empatica+e4/hr+physiological+data+empatica+e4/pm36989502-66-5-4
Average 90 stars, based on 1 article reviews
Hr Physiological Data Empatica E4, supplied by Empatica Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/physiological+data+empatica+e4/hr+physiological+data+empatica+e4/pm36989502-66-5-4
Average 90 stars, based on 1 article reviews
hr physiological data empatica e4 - by Bioz Stars,
2026-09
90/100 stars
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other:Article Title: Balancing Between Privacy and Utility for Affect Recognition Using Multitask Learning in Differential Privacy–Added Federated Learning Settings: Quantitative Study Article Snippet: In the WESAD dataset, each participant recorded physiological signals such as blood volume pulse, electrocardiogram (ECG), EDA, electromyogram, respiration, body temperature, and 3-axis acceleration measured from the chest and wrist using Plux RespiBAN and Article Title: A PPG Signal Dataset Collected in Semi-Naturalistic Settings Using Galaxy Watch Article Snippet: To address this gap, this study presents GalaxyPPG, a dataset collected from 24 participants that includes wrist-worn PPG signals from a Galaxy Watch 5 and an Article Title: EEG and Physiological Signals Dataset from Participants during Traditional and Partially Immersive Learning Experiences in Humanities Article Snippet: • Data format: – Physiological data from OpenBCI and Article Title: MSPTDfast: An Efficient Photoplethysmography Beat Detection Algorithm Article Snippet: The data consisted of wrist PPG signals acquired using an Article Title: Integrating Biofeedback and Artificial Intelligence into eXtended Reality Training Scenarios: A Systematic Literature Review Article Snippet: Also, Wilson et al. (2021) observed that many applications can get “good-enough” results using only the sensors from the Derivative Assay:Article Title: Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic Review Article Snippet: (Rykov et al., 2021) [ ] Predicting workforce depression , 267 , ❖ Fitbit Charge 2 Steps, HR, sleep metrics, circadian rhythm metrics (e.g., inter-daily stability and autocorrelation) , ❖ Binary classification ● Dropouts meet Multiple Additive Regression Trees ● 80% accuracy, 82% sensitivity, and 78% specificity , IW , ● Labels: depressive symptom severity assessed using the 9-item PHQ-9 ● 2 labels/participant (PHQ-9 scores at baseline and after 14 days) ● Monitoring: 14 days , ● Workforce-specific cohort limits generalizability ● Findings apply mainly to balanced demographic subgroups; broader testing needed ● Self-reported depression assessments may introduce response bias. .. (Sato et al., 2023) [ ] Enhanced MDD screening using SQIs to filter motion artifacts , 69 , Activity Assay:Article Title: Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic Review Article Snippet: (Rykov et al., 2021) [ ] Predicting workforce depression , 267 , ❖ Fitbit Charge 2 Steps, HR, sleep metrics, circadian rhythm metrics (e.g., inter-daily stability and autocorrelation) , ❖ Binary classification ● Dropouts meet Multiple Additive Regression Trees ● 80% accuracy, 82% sensitivity, and 78% specificity , IW , ● Labels: depressive symptom severity assessed using the 9-item PHQ-9 ● 2 labels/participant (PHQ-9 scores at baseline and after 14 days) ● Monitoring: 14 days , ● Workforce-specific cohort limits generalizability ● Findings apply mainly to balanced demographic subgroups; broader testing needed ● Self-reported depression assessments may introduce response bias. .. (Sato et al., 2023) [ ] Enhanced MDD screening using SQIs to filter motion artifacts , 69 , |