Passive biosensors successfully monitored neurological disease-related symptoms in patients with multiple sclerosis (MS) both in the clinic and in the wild. This is evident from the study results published in NPJ Digital Medicine.
The study researchers attempted to evaluate the feasibility and correlation of wearable biosensors with traditional measures for clinical disability in MS patients. They recruited patients (N = 25) with MS at Brigham and Women’s Hospital for this ongoing prospective longitudinal study. CAM devices (Cardiac and Activity Monitor) assessed acceleration, movement, heart rate, skin impedance, body temperature and environmental influences. The researchers examined patients in the clinic three times with patients performing tasks while wearing the CAM device on 9 parts of the body. Between the last two clinic visits, patients were given wrist, ankle, and sternum CAM devices and were instructed to keep the devices on for 8 weeks during the day and overnight.
92 percent of the participants were women, with a mean age of 47 years and an average of 16 years since diagnosis of MS. The mean EDSS (Extended Disability Status Scale) value at the start of the study was 3.4 (range 1.0-6.5).
In the clinic’s internal assessment of the 23 mobility categories, the EDSS scores and the MS Functional Composite-4-Scores (MSFC-4) correlated with several features derived from the biosensor, including gait measurements of standing time (EDSS: r, 0.677; P =) 0.01 ; MSFC-4: r, -0.546; P = 0.0070) and mobility activity time (EDSS: r, 0.814; MSFC-4: r, -0.859; P = 0.01 for both) and equilibrium measurements of left-right fluctuation distance (EDSS: r, 0.568; P = 0 , 05; MSFC-4: r, -0.532; P = 0.01) and anterior-posterior fluctuation distance (EDSS: r, 0.503; P = 0.05; MSFC -4: r, -0.489; P = 0.05 ).
During the 8-week free life assessment, study researchers collected approximately 50,000 hours of data. Several of the correlations with MSFC-4 scores were repeated, including gait hold time (r, -0.56; P = 0.0055), breast rotation angle (r, 0.44; P = 0.0377), and mean delay the psychomotor vigilance task (r) -0.55; P = 0.0060). The results showed that additional measured traits correlated with the MSFC-4 scores, such as: B. Leg movement during sleep (r, -0.45; P = 0.0398) and total idle minutes (r, -0.52; P = 0.0110).
Participants appeared to be happy with the way they were wearing the sensors, which suggests that most (87%) others would recommend taking part in a similar body sensor study. The most frequently reported difficulties were charging the sensors (40%), followed by issues with usability (27%).
This study was limited by its retention and participation rates (4 participants did not complete all clinic visits, 10 did not complete the final survey, and 7 were not very compliant when wearing the sensors at home).
The study’s researchers concluded that the wearable biosensors “provide metrics with good correlations to complex MS scales that are traditionally assessed by a neurologist” and that the results “highlight the feasibility of using passive biosensor measurement techniques to monitor disability in MS patients both in the clinic and in the independent clinic. Living environment. ”
Chitnis T., Gloss BI, Gonzalez C. et al. Quantifying neurological diseases using biosensor measurements in the clinic and in the wild in multiple sclerosis. NPJ Digit Med. 2019; 2 (1): 123. doi: 10.1038 / s41746-019-0197-7