Validity and reliability study of a novel surface electromyography sensor using a well-consolidated electromyography system in individuals with cervical spinal cord injury.

STUDY DESIGN: Non-interventional, cross-sectional pilot study. OBJECTIVES: To establish the validity and reliability of the BioStamp nPoint biosensor (Medidata Solutions, New York, NY, USA [formerly MC10, Inc.]) for measuring electromyography in individuals with cervical spinal cord injury (SCI) by comparing the surface electromyography (sEMG) metrics with the Trigno wireless electromyography system (Delsys, Natick, MA, USA). SETTING: Participants were recruited from the Shirley Ryan AbilityLab registry. METHODS: Individuals aged 18-70 years with cervical SCI were evaluated with the two biosensors to capture activity on upper-extremity muscles during two study sessions conducted over 2 days (day 1-consent alone; day 2-two data collections in same session). Time and frequency metrics were captured, and signal-to-noise ratio was determined for each muscle group. Test-retest reliability was determined using Pearson's correlation. Validation of the BioStamp nPoint system was based on Bland-Altmann analysis. RESULTS: Among the 11 participants, 30.8% had subacute cervical injury at C5-C6; 53.8% were injured within 1 year of the study. Results from the test-retest reliability assessment revealed that most Pearson's correlations between the two sensory measurements were strong (≥0.50). The Bland-Altman analysis found values of the signal-to-noise ratio, frequency, and peak amplitude were within the level of agreement. Signal-to-noise ratios ranged from 7.06 to 22.1. CONCLUSIONS: In most instances, the performance of the BioStamp nPoint sensors was moderately to strongly correlated with that of the Trigno sensors in all muscle groups tested. The BioStamp nPoint system is a valid and reliable approach to assess sEMG measures in individuals with cervical SCI. SPONSORSHIP: The present study was supported by AbbVie Inc.

A Pivotal Study to Validate the Performance of a Novel Wearable Sensor and System for Biometric Monitoring in Clinical and Remote Environments.

BACKGROUND: Increasingly, drug and device clinical trials are tracking activity levels and other quality of life indices as endpoints for therapeutic efficacy. Trials have traditionally required intermittent subject visits to the clinic that are artificial, activity-intensive, and infrequent, making trend and event detection between visits difficult. Thus, there is an unmet need for wearable sensors that produce clinical quality and medical grade physiological data from subjects in the home. The current study was designed to validate the BioStamp nPoint® system (MC10 Inc., Lexington, MA, USA), a new technology designed to meet this need. OBJECTIVE: To evaluate the accuracy, performance, and ease of use of an end-to-end system called the BioStamp nPoint. The system consists of an investigator portal for design of trials and data review, conformal, low-profile, wearable biosensors that adhere to the skin, a companion technology for wireless data transfer to a proprietary cloud, and algorithms for analyzing physiological, biometric, and contextual data for clinical research. METHODS: A prospective, nonrandomized clinical trial was conducted on 30 healthy adult volunteers over the course of two continuous days and nights. Supervised and unsupervised study activities enabled performance validation in clinical and remote (simulated "at home") environments. System outputs for heart rate (HR), heart rate variability (HRV) (including root mean square of successive differences [RMSSD] and low frequency/high frequency ratio), activity classification during prescribed activities (lying, sitting, standing, walking, stationary biking, and sleep), step count during walking, posture characterization, and sleep metrics including onset/wake times, sleep duration, and respiration rate (RR) during sleep were evaluated. Outputs were compared to FDA-cleared comparator devices for HR, HRV, and RR and to ground truth investigator observations for activity and posture classifications, step count, and sleep events. RESULTS: Thirty participants (77% male, 23% female; mean age 35.9 ± 10.1 years; mean BMI 28.1 ± 3.6) were enrolled in the study. The BioStamp nPoint system accurately measured HR and HRV (correlations: HR = 0.957, HRV RMSSD = 0.965, HRV ratio = 0.861) when compared to ActiheartTM. The system accurately monitored RR (mean absolute error [MAE] = 1.3 breaths/min) during sleep when compared to a Capnostream35TM end-tidal CO2 monitor. When compared with investigator observations, the system correctly classified activities and posture (agreement = 98.7 and 92.9%, respectively), step count (MAE = 14.7, < 3% of actual steps during a 6-min walk), and sleep events (MAE: sleep onset = 6.8 min, wake = 11.5 min, sleep duration = 13.7 min) with high accuracy. Participants indicated "good" to "excellent" usability (average System Usability Scale score of 81.3) and preferred the BioStamp nPoint system over both the Actiheart (86%) and Capnostream (97%) devices. CONCLUSIONS: The present study validated the BioStamp nPoint system's performance and ease of use compared to FDA-cleared comparator devices in both the clinic and remote (home) environments.