Publications using Empatica's technology

In partnership with dozens of top researchers and hospitals, we are pioneering new ways to care for patients and enable research breakthroughs. Thousands of publications have been made possible due to our technology. Here you can find a selection of these studies.

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Enhance your research with the Empatica Health Monitoring Platform

Conducting research at scale from patients’ homes has never been easier, with raw data and digital biomarkers of the highest quality, and a full-stack platform designed to reduce patient and site burden.

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Publications using Empatica's technology

Enhance your research with the Empatica Health Monitoring Platform

Wondering if our solutions and digital biomarkers fit your needs?

Our technology has been validated in research studies and trials across neurology, mental and physical health, sleep, oncology, and more

Using Wearables in Mental Health Care for Children and Adolescents: A Scoping Review

Empatica E4 wristband assessment of probable REM sleep behavior disorder in people with Parkinson's disease. Results from the DIGI.PARK study

Seizure burden and treatment efficacy evaluation in anti-LGI1 autoimmune encephalitis patients using wearable device: a pilot feasibility study

Predicting Sleep Quality via Unsupervised Learning of Cardiac Activity

Monitoring differences in the function of the autonomic nervous system in patients with chronic insomnia using a wearable device

Urban environment influences on stress, autonomic reactivity and circadian rhythm: protocol for an ambulatory study of mental health and sleep

Evaluating reliability in wearable devices for sleep staging

Addressing Wearable Sleep Tracking Inequity: A New Dataset and Novel Methods for a Population with Sleep Disorders

DREAMT: Dataset for Real-time sleep stage EstimAtion using Multisensor wearable Technology

State of the science and recommendations for using wearable technology in sleep and circadian research

Sleep Classification With Artificial Synthetic Imaging Data Using Convolutional Neural Networks

The Role of Model Personalization for Sleep Stage and Sleep Quality Recognition Using Wearables

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