Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease

Abstract

Background: Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD).

Methods: Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance.

Results: Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners.

Conclusion: A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.

Keywords: Adherence; Cerebrovascular disease; Neurodegenerative disease; Remote monitoring; User acceptance; Wearable sensors.

Fig. 1

Multi-modal, multi-nodal device–sensor relationship and participant set up. a Limb (GENEActiv) and chest (Bittium Faros 180) devices worn within this study, with the corresponding sensors and body location(s) and b Schematic representation of device location on body segments. The multi-modal, multi-nodal approach enables simultaneous assessment of multiple domains of health in persons living with cerebrovascular and neurodegenerative disease

Fig. 2

Participants’ average non-wear rate by wear location (n = 37). The data collection window was defined as 2:00 pm on the day of the baseline visit to 2:00 pm on Day 4, resulting in four consecutive 24-h periods. Grey symbols denote individual participants. Black symbols denote the four participants deemed to be outliers across two or more wear locations. White symbols denote participant outliers for a single wear location. Non-wear rate was significantly different dependent upon wear location (p = 0.006) and post-hoc testing revealed a significant difference between the chest compared to the left wrist (p = 0.03) and right wrist (p = 0.02). Note: symbols appearing across figures do not denote the same participant

Fig. 3

Non-wear rate based on time of day (a) and day of collection (b) (n = 37). Data represent periods of time when less than three devices were worn (multi-sensor non-wear). The data collection window in these analyses was defined as 2:00 pm on the day of the baseline visit to 2:00 pm on Day 6, resulting in six consecutive 24-h periods. Black symbols denote the participants deemed to be outliers across two or more data points. White symbols denote participant outliers for a single data point. Non-wear rate was significantly different based on time of day (p < 0.001) and increased across the wear period (p = 0.04)

Fig. 4

Pattern and total rate of non-wear across and within individual study participants (n = 37). Data represent periods of time when less than three devices were worn (multi-sensor non-wear). a Total non-wear rates for each participant, sorted from least (top) to most (bottom) and b Non-wear periods for each day of data collection. Width of the bar denotes bout duration. Shaded grey sections denote nighttime periods (11:00 pm to 7:00am)