Abstracts

Rationale: A wireless motion-detection technology developed at the Massachusetts Institute of Technology utilizes a novel low radiofrequency (RF) emission/sensing system and machine learning algorithms to isolate a patient’s movement with unprecedented sensitivity and spatial resolution. It has been validated to track patient gait and respiratory effort. We hypothesize this device may detect convulsive seizures and peri-ictal apnea, two major risk factors of sudden unexpected death in epilepsy (SUDEP). This device overcomes limitations of current technologies for detection of seizures and SUDEP risk factors, as this system does not require the patient to wear and maintain a device continuously, and RF signals may be analyzed through barriers without requiring line-of-sight.

Methods: We conducted a prospective study of patients ≥18 years old with focal and/or generalized epilepsy admitted to the epilepsy monitoring unit of the Brigham and Women’s Hospital between July of 2021 and May of 2022. Video-EEGs were recorded using the International 10-20 System. Respiratory inductive plethysmography (RIP) belts were placed to assess the chest wall and abdominal excursions in patients who were expected to have convulsions. Reconstructed RF signals corresponding to peri-ictal movements were visually analyzed as a function of distance from the device in patient space and correlated in time with seizure onset and termination determined by video-EEG analysis.

Results: A total of 60 patients underwent simultaneous video-EEG and RF recording, and 9 patients were connected to RIP belts. A total of ten convulsions were captured on video-EEG. The device revealed RF signal changes in 9/10 (90%) convulsions from 8 patients and identified the onset of the motor activity with a specific unique RF pattern (Figure 1). Interictal respiratory patterns from the RF-device correlated accurately to the RIP-based patterns (Figure 2). Artifact from convulsive movements limited analysis of RF-based respiratory signals during the ictal period. Postictal apnea has not yet been recorded in any patients.

Conclusions: The RF-device was able to accurately identify convulsions with unique RF heat map signatures that discriminate from non-specific motor activity. In addition, the RF-device was able to detect respiratory effort interictally, though movement artifacts prevented the isolation of ictal respiratory patterns.

Funding: None