Validation of a wireless patch sensor to monitor mobility tested in both an experimental and a hospital setup: A cross-sectional study

Abstract

PurposeTo assess the concurrent validity of a wireless patch sensor to monitor time lying, sitting/standing, and walking in an experimental and a hospital setup.MethodsHealthy adults participated in two testing sessions: an experimental and real-world hospital setup. Data on time lying, sitting/standing, and walking was collected with the HealthPatch and concurrent video recordings. Validity was assessed in three ways: 1. test for mean differences between HealthPatch data and reference values; 2. Intraclass Correlation Coefficient analysis (ICC 3.1 agreement); and 3. test for mean differences between posture detection accuracies.ResultsThirty-one males were included. Significant mean differences were found between HealthPatch data and reference values for sitting/standing (mean 14.4 minutes, reference: 12.0 minutes, p<0.01) and walking (mean 6.4 minutes, reference: 9.0 minutes, p<0.01) in the experimental setup. Good correlations were found between the HealthPatch data and video data for lying (ICC: 0.824) and sitting/standing (ICC: 0.715) in the hospital setup. Posture detection accuracies of the HealthPatch were significantly higher for lying and sitting/standing in the experimental setup.ConclusionsOverall, the results show a good validity of the HealthPatch to monitor lying and poor validity to monitor sitting/standing or walking. In addition, the validity outcomes were less favourable in the hospital setup.

Exploring barriers to physical activity of patients at the internal medicine and surgical wards: a retrospective analysis of continuously collected data

“…For example, it is possible that 0.1 h daily walking (as presented in our study) might actually represent up to 0.4 h daily walking. However, the main conclusions of this study are based on the time spent lying during the daytime, which has been validated in terms of accuracy in previous work [23]. Additionally, our study included a relatively small sample (n < 50 patients) [33], and our results will need to be confirmed by larger prospective studies.…”

“…Subsequently, data were stored instantly on an online secured cloud. Previous research on the HealthPatch V R in an experimental and hospital setting showed adequate validity for measuring time lying and sitting/standing [23]. The posture detection accuracy of the HealthPatch V R was less accurate during walking.…”

“…Limitations of this study include the known error margins (established in previous research) of the HealthPatch V R for measuring physical activity [23]. Readers should note that outcomes regarding time walking might be underestimated.…”

“…Strengths of this study include the method of measurement: physical activity was continuously monitored during hospital stay with a wearable patch, including an accelerometer with known psychometric properties [23]. Thus, the results were unlikely to be influenced by socially desirable behaviour of patients or researchers, as data were collected more or less invisibly in the context of a feasibility study and analysed retrospectively [28].…”

Optimization and Validation of a Classification Algorithm for Assessment of Physical Activity in Hospitalized Patients

“…Fifty patients were enrolled after signing the informed consent. The sample size of 50 corresponds to that used in previous validation studies, which included 8 to 99 participants [ 35 , 42 , 46 , 62 , 65 , 66 , 67 , 68 , 69 , 70 ]. Optimization of the adjustable algorithm described by Bijnens et al was performed on data of 25 patients [ 49 ].…”