Discover the applications and benefits of remote health monitoring to effectively decentralize clinical trials.
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Reduce patient and site burden while enhancing data quality. Use industry-leading wearable technology and validated digital biomarkers to collect data remotely, continuously, and unobtrusively, with easy access via the cloud.
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Combining award-winning design, state-of-the-art sensors, and unprecedented flexibility, Empatica’s clinical trials solution is a modular platform that enables data to be accessed and downloaded both in an uncomputed raw format and in the shape of digital biomarkers, freeing up research and health monitoring needs to go as deep or as broad as needed.
Conducting trials at scale from patients’ homes has never been easier.
The Sleep Revolution, an interdisciplinary international research and development project, aims to develop a smart, personalized diagnostic and therapeutic solution for sleep-disordered breathing (sleep apnea). Using the EmbracePlus smartwatch, the study entails developing Machine Learning models to determine the severity and treatment needs of people with sleep apnea, for accurate diagnosis and improved treatment.
TIMESPAN, a consortium of 17 institutions from 14 countries has launched the ART-CARMA project, to study the management of chronic cardiometabolic disease and treatment discontinuity in adult ADHD patients. Using EmbracePlus, the project aims to understand the risks of cardiometabolic illnesses such as cardiovascular disease and obesity for adults with ADHD, and how their future health can best be improved through medication.
VeraSci’s Innovation Lab has been conducting an NIH-funded study examining the relationship between real-time measurements of gait and actigraphy, collected by the Embrace2, and established cognitive and functional endpoints that are sensitive to decline early in the Alzheimer’s disease continuum. Their preliminary data suggest a positive correlation between in-clinic measurements and the endpoints developed using Embrace2 data for monitoring the patient's cognitive health.
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Sunovion Pharmaceuticals utilized Empatica Health Monitoring Platform during their international multi-site phase-4 anti-epileptic drug trial. Empatica’s FDA-cleared seizure detection algorithm and the e-diary app allowed Sunovion to continuously monitor patients, gaining an objective insight into seizure counts while remotely monitoring compliance throughout the study.
The US government’s Biomedical Advanced Research and Development Authority (BARDA) has partnered with Empatica to develop a digital endpoint for detecting the earliest signs of the flu. Through the use of the Embrace2 wearable and Empatica data analysis expertise, they engaged in a prospective study monitoring healthy individuals throughout the flu season with the aim to develop an early detection system. Following the outbreak of the Covid-19 pandemic, BARDA and Empatica renewed their partnership to utilize EmbracePlus and the Care suite for Covid-19 early detection.
Harvard University Clinical Psychologist Dr. Matthew K. Nock is using Embrace for Research to detect digital phenotypes related to suicidal thoughts in a multi-site study involving hundreds of individuals wearing Embrace2. This is the largest-yet study about suicidal behavior also measuring skin conductance levels as an objective way to assess changes in physiological distress in the participants.
4YouandMe, a non-profit company founded by Dr. Stephen H. Friend has partnered with clinicians at Oxford University and Mount Sinai School of Medicine to conduct a multi-site prospective cohort study, utilizing Empatica wearables to monitor signs of stress and symptoms of Crohn's disease. The aim of this project is to provide biofeedback to patients with Crohn’s, in order to potentially prevent negative clinical changes in their condition.
MIT Media Lab’s doctoral student, Kristina T. Johnson has embarked on a journey to measure autonomic changes in parabolic flyers. Parabolic flight planes are notorious for inducing high levels of nausea. By using Empatica’s technology and other biosignal measures, Kristy and her team were able to gain an objective insight into novice and veteran flyers’ physiological well-being during flights.
Pear Therapeutics, the leader in prescription digital therapeutics, is using Empatica’s technology to explore using wearable sensors in the evaluation of withdrawal symptoms in patients with substance use disorder (SUD), opioid use disorder (OUD), and alcohol use disorder (AUD). Using the EmbracePlus smartwatch, Pear Therapeutic aims to integrate real-time personalization of digital therapeutic content and pharmaceutical dosing to patients across disease stages.
Our data science legacy and MIT origins ensure our solution is built with data scientists’ needs in mind. Data come in an accessible, uncomputed raw format, or as validated digital biomarkers, and are instantly ready for analysis.
EmbracePlus is built in partnership with NASA, the USAMRDC and HHS. Our FDA-cleared Embrace2 is used by thousands of people who live with epilepsy, while our E4 wristband has helped publish over 1,000 academic papers.
EmbracePlus has been designed to be a pleasure for patients to wear, making it the missing link between medical devices and consumer wearables.
We provide accelerated timelines, with immediate deployment and dedicated onboarding that can be delivered within weeks.
All our clients benefit from dedicated onboarding, an account manager, and site support to walk you through every step of the process
We handle the logistics and provide IRB materials so you can focus on your research
Dedicated customer and technical support across continents, providing prompt assistance when needed
Start collecting data in less than 5 minutes with auto-generated, secure QR codes for patient enrollment
The Empatica platform is entirely created in-house, from the hardware and software, to the SDK and cloud infrastructure that gather and store the data, making it a fully integrated and flexible solution that adapts to your research needs.
EmbracePlus continuously measures and records physiological parameters, which are sent via Bluetooth® to the Care app
The Care app uses the phone’s internet connection to automatically transfer all data to the Empatica cloud
The cloud securely stores data and makes it available for immediate access, either via direct download or through online visualization on the Care Portal
The Care Portal allows you to manage your studies and visualize data and biomarkers over time, and across sites
EmbracePlus continuously measures and records physiological parameters, which are sent via Bluetooth® to the Care app
The Care app uses the phone’s internet connection to automatically transfer all data to the Empatica cloud
The cloud securely stores data and makes it available for immediate access
Access your data directly from your cloud, both in raw format and as digital biomarkers
EmbracePlus continuously measures and records physiological parameters, which are sent via Bluetooth® to a companion app
Build your own custom app using the Empatica SDK, to process, visualize and stream EmbracePlus data as you wish
Implement in your own infrastructure, or access your data directly from your cloud, both in raw format and as digital biomarkers
Sensor modes are predefined configurations for EmbracePlus that enable the device to focus on collecting specific parameters that are key to your study. Talk to our team to find out how sensor modes can enhance the data collection capabilities of the Empatica Health Monitoring Platform.
Using Electronic Data Capture (EDC) can result in significant savings throughout all the phases of clinical trials. This graph illustrates an estimation of how much a pharmaceutical company can save per patient in each phase if using a solution like Empatica’s.
Total saving per patient
(Phase I)
Total saving per patient
(Phase I and II)
Total saving per patient
(Phase I, II and III)
We collaborate with the best research teams in the world to advance the understanding of human health in real-life settings. Our work is focused on measuring and quantifying the impact of wearable technology in health, while our products have been used in a breadth of contexts, from large-scale clinical trials to intimate academic studies.
This research aims to bridge the gap between laboratory settings and real-world field studies by introducing a new algorithm that leverages the capabilities of wearable physiological sensors to detect moments of stress (MOS).
Results: our results overall demonstrate that stress can be reliably detected with an accuracy that varies from 75 to 100%, with an average of 84%. [...] the defined critical values are tailored to the current research, they do not serve as global values for stress detection.
The current work examined the use of a wearable sensor to detect self-administration of opioids after dental surgery using machine learning.
Results: results from training and testing model of machine learning indicated that opioid self-administration could be identified with reasonable accuracy, leading to considerable possibilities of the use of wearable technology to advance prevention and treatment.
This study outlines a novel machine learning model which predicts interstitial glucose levels using non-invasive measurements with impressive accuracy.
Results: the study demonstrated the feasibility of using noninvasive and widely accessible methods, including smartwatches and food logs recorded over 10 days, to continuously detect personalized glucose deviations and to predict the exact interstitial glucose value in real time with up to 84% and 87% accuracy, respectively.
The aim of this study is to examine (1) whether an mHealth device integrated into a community mental health team can improve outcomes for young adults with severe mental illness and (2) whether the device detects periods of mental health versus deterioration.
Results: coming at the end of the study.
The study demonstrates that epilpetic and psychogrenic non-epileptic seizures can be discriminated based on signals related to autonomic nervous system activity recorded via wearable sensors.
Results: classification performance achieved a predictive accuracy of 78 ± 1.5% on previously unseen data for whether a seizure was epileptic or psychogenic.
Empatica’s constant and decisive efforts aim at ensuring the safety, effectiveness, and quality of its medical devices as well as providing products that meet customer and applicable statutory and regulatory requirements.
The Empatica Health Monitoring Platform can be purchased with two different plans: Professional or Enterprise. The Enterprise plan is suited to large-scale clinical trials, with a large range of dedicated services to help you make the most of the Platform.
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