To develop and validate a multi-modal digital health technology for remote monitoring of disease symptoms in myasthenia gravis (MG).

MG is a chronic autoimmune neuromuscular disease characterized by muscle weakness and fatigue. Other common symptoms of MG include eye drooping (ptosis), double vision (diplopia), difficulty in chewing, and difficulty in speaking (dysarthria). MG symptoms are typically evaluated by neuromuscular experts through in-person neurologic examinations. These assessments are time-consuming, require disease expertise, and capture only a snapshot in time.

We developed a multi-modal digital health technology (DHT) called BioDigit MG, for monitoring MG symptoms. BioDigit MG includes a set of tablet-guided speech and video-based assessments, electronic patient-reported outcomes relevant to MG, as well as a wearable sensor to measure physical activity and posture during activities of daily living. We assessed the real-world feasibility and acceptability of BioDigit MG by conducting a clinical study with MG patients who used the developed DHT to collect data related to their symptoms. To evaluate technology acceptance and usability, we conducted face-to-face interviews with the MG patients and expert clinicians, each with over 13 years of practice.

The study included 20 MG patients, and 5 expert clinicians. During the study, a total of 219 speech tasks and 119 videos were successfully collected by the DHT, achieving 100% reliability in data collection and transfer. The patient and clinician participants found the DHT highly effective, easy to use, and well-suited to their needs.

The study illustrates the promising role of digital health technologies in revolutionizing the management of Myasthenia Gravis. By providing continuous, objective, and easily accessible monitoring, the BioDigit MG system can potentially enhance the capability to manage MG effectively.