A Wearable-based Solution for Remote Monitoring of Symptoms in Myasthenia Gravis


Clinical Trials

Poster Number: M196


Ashkan Vaziri, PhD, Biosensics LLC, Amanda Guidon, MD, MPH, Massachusetts General Hospital/Harvard, Ram kinker Mishra, PhD, BioSensics LLC, Newton, MA, USA, Adonay Sastre Nunes, PhD, BioSensics LLC, Newton, MA, USA, Petra W. Duda, MD, PhD, UCB Pharma, Cambridge, MA, USA

To develop and validate a digital health solution for remote and frequent assessments of symptoms in Myasthenia gravis (MG).
MG is a chronic autoimmune neuromuscular disorder which causes fatigable skeletal muscle weakness and impairs activities of daily living. Currently, MG symptoms are evaluated by neuromuscular experts through in-person neurologic examinations. These assessments are time-consuming, subjective, require disease expertise, and capture only a snapshot in time. A remote monitoring solution which enables frequent, objective monitoring of key symptom domains in MG and their fluctuations is urgently needed for clinical care.
We developed a wearable-based remote monitoring solution for MG that consists of 1) PAMSys, a patented wearable sensor for monitoring physical activity, 2) a mobile application for collection of i) speech data during different speech tasks, ii) facial videos to assess ptosis, and iii) MG-related patient reported outcomes (e.g., MG-ADL). We interviewed 4 experts that care for MG patients and used their feedback to improve the developed solution.
A mobile application was created, which serves to securely transmit collected data to a backend server, and offer auditory guidance throughout the recording process. Additionally, we developed proprietary pipelines to analyze the collected voice and video data to identify crucial eye landmarks and process speech. A clinical study is ongoing, aiming to recruit 20 individuals diagnosed with MG, who will be monitored for 7 days at home using the PAMSys sensor, and using the developed solution to collect speech and facial videos. Result from this study will be used to examine the correlations between MG outcome measures and data collected and measured using the PAMSys sensor and mobile application.
A robust wearable-based remote monitoring solution is developed to enable frequent assessment of symptoms in MG. Our proprietary pipelines for data analysis show significant potential for objective symptom assessment.