Biosensor vital sign detects multiple sclerosis progression.

Area of Science:

• Neurology
• Biomedical Engineering
• Wearable Technology

Background:

• Multiple Sclerosis (MS) diagnosis and monitoring rely on clinical assessments which can be subjective.
• Differentiating between relapsing and progressive forms of MS is crucial for treatment decisions.
• Objective, sensitive measures of disease progression and limb function in MS are needed.

Purpose of the Study:

• To evaluate a wearable multisensor device for differentiating progressive versus relapsing multiple sclerosis (MS).
• To assess the device's ability to capture short-term limb progression in MS patients.
• To explore the potential of this technology as a novel outcome measure in MS.

Main Methods:

• Prospective study of MS patients (N=68) over approximately 6-month intervals.
• Participants performed finger and foot taps using a MYO-band wearable sensor.
• Analysis of accelerometer, gyroscope, and EMG data to derive limb progression metrics (UE/LE).
• Receiver Operating Characteristic (AUROC) analysis for discrimination and Pearson correlation with EDSS scores.

Main Results:

• The multisensor algorithm successfully differentiated relapsing from secondary progressive MS with high accuracy (AUROC UE 0.93, LE 0.96).
• Derived metrics showed significant association with baseline Expanded Disability Status Scale (EDSS) scores (P < 0.001).
• The device detected limb function changes indicative of progression in some patients over a short follow-up period.

Conclusions:

• A novel wearable multisensor algorithm can distinguish between progressive and relapsing MS.
• The device captures subtle changes in limb function, serving as a potential "MS vital sign".
• This noninvasive, user-friendly technology is adaptable for clinical practice and trials, with potential for other neurological conditions.