Dr. Dhruv Sheshadri's research involves the development, validation, and translation of wearable technology, bioelectronic devices, and digital therapeutics targeting human health and performance. This research has been dessemianted in journals such as NPJ Digital Medicine, Circulation, Journal of the American Academy of Dermatology, and IEEE and reported in news outlets such as CNN, Wall Street Journal, Forbes, Fortune, Wired UK, and Nature Outlook. His research has been funded by grants from the Department of Defense, Northwestern University, National Science Foundation, and American Orthopedic Society for Sports Medicine for developing, translating, and commercializing wearable technology.
Background
The management of movement disorders, like Parkinson’s disease and essential tremor, relies on accurately tracking symptom severity. Continuous physiological monitoring is also critical for managing preeclampsia and substance withdrawal. There is a profound need for objective, longitudinal data collection that captures a patient's status outside the clinical setting. Clinicians require uninterrupted insights into daily symptom fluctuations, including early-morning and sleep-phase events, to evaluate disease progression and tailor medication dosages. Continuous monitoring provides a comprehensive picture of a patient's state throughout their normal routines.
Despite this need, current monitoring approaches suffer from significant limitations. Traditional clinical assessments are inherently episodic, offering only brief snapshots of a patient’s condition, and heavily depend on subjective, often inaccurate patient diaries. While commercial wearables attempt to fill this void, they present critical flaws. Existing devices typically exhibit low tremor detection accuracy, often around 75%, struggling to distinguish pathological tremors from normal daily activities or motion artifacts. Furthermore, current wearables are plagued by battery life constraints. Patients must routinely remove these devices for charging, creating substantial data gaps that prevent true continuous monitoring and obscure vital symptom occurrences.
Technology Overview
This wrist-worn medical monitoring device and software ecosystem provides continuous tracking of movement disorders. The hardware features a modular housing containing a microcontroller, internal batteries, a heart rate sensor, and motion sensors. To ensure uninterrupted data collection, the device utilizes a snap-on external battery pack that connects via USB-C, allowing for 24/7 operation. Collected data is transmitted to a cloud-based platform where it is processed. Patients and clinicians access this information through a mobile application and online dashboard, which include tools for medication logging, symptom tracking, and an AI-powered chatbot.
This technology is highly differentiated by its ability to overcome the critical limitations of traditional clinical assessments and existing commercial wearables. Unlike standard devices that suffer from data gaps during charging cycles, the hot-swappable external battery module enables true continuous monitoring without removing the wearable. Furthermore, the solution employs a proprietary multi-modal data fusion algorithm that combines heart rate and motion data. This unique approach effectively filters out motion artifacts to distinguish pathological tremors from normal daily activities, significantly surpassing the industry-standard 75% detection accuracy. By integrating gap-free data collection with a hierarchical clinical workflow platform, the system empowers physicians to perform precise, data-driven medication titration.
Benefits
- Enables true 24/7, uninterrupted patient monitoring without data gaps through a novel hot-swappable external battery module.
- Delivers highly accurate tremor detection by utilizing a proprietary multi-modal algorithm that combines heart rate and motion data to filter out daily motion artifacts.
- Provides clinicians with objective, longitudinal data to replace subjective patient diaries, facilitating precise, data-driven medication titration and remote patient monitoring.
- Offers a comprehensive software ecosystem featuring a hierarchical clinical dashboard and a patient-facing mobile app with medication logging, symptom tracking, and an AI chatbot.
- Serves as a versatile platform for multiple medical applications, including movement disorder management, clinical trial digital endpoints, preeclampsia monitoring, and substance withdrawal tracking.
- Ensures reliable physiological readings via an ergonomic, modular hardware design that maintains consistent, direct skin contact with the sensors.
Applications
- Movement disorder continuous monitoring
- Clinical trial digital endpoints
- Maternal health preeclampsia monitoring
- Substance withdrawal symptom management
- Remote medication efficacy tracking