Sen-Gupta Ellora, Wright Donald E, Caccese James W, Wright John A, Jortberg Elise, Bhatkar Viprali, Ceruolo Melissa, Ghaffari Roozbeh, Clason Dennis L, Maynard James P, Combs Arthur H
MC10 Inc., Lexington, Massachusetts, USA.
Northwestern University, Evanston, Illinois, USA.
Digit Biomark. 2019 Mar 1;3(1):1-13. doi: 10.1159/000493642. eCollection 2019 Jan-Apr.
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.
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.
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.
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 Actiheart. The system accurately monitored RR (mean absolute error [MAE] = 1.3 breaths/min) during sleep when compared to a Capnostream35 end-tidal CO 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.
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.
越来越多的药物和器械临床试验将活动水平及其他生活质量指标作为治疗效果的终点进行追踪。传统的试验要求受试者间歇性地前往诊所，这种方式不自然、活动密集且频率低，使得在访视期间难以进行趋势和事件检测。因此，迫切需要一种可穿戴传感器，能够在受试者家中收集临床质量和医学级别的生理数据。本研究旨在验证BioStamp nPoint®系统（美国马萨诸塞州列克星敦市的MC10公司），这是一种旨在满足这一需求的新技术。
评估一种名为BioStamp nPoint的端到端系统的准确性、性能和易用性。该系统包括一个用于试验设计和数据审查的研究者门户、贴合皮肤的保形、低轮廓可穿戴生物传感器、用于将无线数据传输到专有云的配套技术，以及用于分析临床研究中的生理、生物特征和情境数据的算法。
对30名健康成年志愿者进行了一项为期两天两夜的前瞻性、非随机临床试验。通过有监督和无监督的研究活动，在临床和远程（模拟“在家”）环境中对系统性能进行验证。评估了系统输出的心率（HR）、心率变异性（HRV）（包括逐次差值的均方根[RMSSD]和低频/高频比值）、规定活动期间的活动分类（躺、坐、站、走、固定自行车骑行和睡眠）、步行时的步数计数、姿势特征以及睡眠指标，包括入睡/醒来时间、睡眠时间和睡眠期间的呼吸频率（RR）。将输出结果与经美国食品药品监督管理局（FDA）批准的用于HR、HRV和RR的对比设备进行比较，并与研究者对活动和姿势分类、步数计数以及睡眠事件的实际观察结果进行比较。
30名参与者（77%为男性，23%为女性；平均年龄35.9±10.1岁；平均体重指数28.1±3.6）纳入研究。与Actiheart相比，BioStamp nPoint系统能够准确测量HR和HRV（相关性：HR = 0.957，HRV RMSSD = 0.965，HRV比值 = 0.861）。与Capnostream35潮气末二氧化碳监测仪相比，该系统在睡眠期间能够准确监测RR（平均绝对误差[MAE] = 1.3次呼吸/分钟）。与研究者的观察结果相比，该系统能够高精度地正确分类活动和姿势（一致性分别为98.7%和92.9%）、步数计数（MAE = 14.7，在6分钟步行期间占实际步数的<3%）以及睡眠事件（MAE：入睡 = 6.8分钟，醒来 = 11.5分钟，睡眠时间 = 13.7分钟）。参与者表示该系统的易用性为“良好”至“优秀”（系统可用性量表平均得分为81.3），并且与Actiheart（86%）和Capnostream（97%）设备相比，更倾向于BioStamp nPoint系统。
本研究验证了BioStamp nPoint系统在临床和远程（家庭）环境中与经FDA批准的对比设备相比的性能和易用性。
