Wearable Sensor Technology to Measure Physical Activity (PA) in the Elderly

Mapping the extent of the literature and psychometric properties for the Physical Activity Scale for the Elderly (PASE) in community-dwelling older adults: a scoping review

BACKGROUND

Identifying valid and accessible tools for monitoring and improving physical activity levels is essential for promoting functional ability and healthy aging. The Physical Activity Scale for the Elderly (PASE) is a commonly used and recommended self-report measure of physical activity in older adults. The objective of this scoping review was to map the nature and extent to which the PASE has been used in the literature on community-dwelling older adults, including the evidence for its psychometric properties.

METHODS

Seven electronic databases (MEDLINE (Ovid), Embase (Ovid), AMED (Ovid), Emcare (Ovid), CINAHL (EBSCO), Ageline (EBSCO)) were searched from inception to January 25, 2023. Studies were included if physical activity was part of the aim(s) and measured using the PASE, participants had a mean age of 60 years or older and lived in the community, and papers were peer-reviewed journal articles published in English. Pairs of independent reviewers screened abstracts, full-texts, and extracted data. Where possible, weighted mean PASE scores were calculated for different subgroups based on age, sex, and clinical population.

RESULTS

From 4,124 studies screened, 232 articles from 35 countries met the inclusion criteria. Most studies were cross-sectional (60.78%), completed in high-income countries (86.4%) and in North America (49.57%). A variety of clinical conditions were included (n = 21), with the most common populations being osteoarthritis (n = 13), Parkinson's disease (n = 11), and cognitive impairment (n = 7). Psychometric properties of ten versions of the PASE were found. All versions demonstrated acceptable test-retest reliability. Evidence for construct validity showed moderate correlations with self-reported physical activity, fair to moderate with accelerometry derived activity and fair relationships with physical function and self-reported health. Pooled means were reported in graphs and forest plots for males, females, age groups, and several clinical populations.

CONCLUSION

The PASE was widely used in a variety of clinical populations and geographical locations. The PASE has been culturally adapted to several populations and evaluated for its reliability and convergent validity; however, further research is required to examine responsiveness and predictive validity. Researchers can use the weighted mean PASE scores presented in this study to help interpret PASE scores in similar populations. OSF REGISTRATION: osf.io/7bvhx.

The impact of age on physical functioning after treatment for breast cancer, as measured by patient-reported outcome measures: A systematic review

PURPOSE

This systematic review aims to explore the impact of age on physical functioning post-treatment for early-stage, locally advanced, or locally recurrent breast cancer, as measured by patient-reported outcome measures (PROMs), identify PROMs used and variations in physical functioning terms/labels.

METHODS

MEDLINE, EmBase, PsycINFO, CINAHL and AMED were searched, along with relevant key journals and reference lists. Risk of bias (quality) assessment was conducted using a Critical Appraisal Skills Programme checklist. Data was synthesised through tables and narrative.

RESULTS

28,207 titles were extracted from electronic databases, resulting in 44 studies with age sub-groups, and 120 without age sub-groups. Of those with findings on the impact of age, there was variability in the way findings were reported and 21 % found that age did not have a significant impact. However, 66 % of the studies found that with older age, physical functioning declined post-treatment. Comorbidities were associated with physical functioning declines. However, findings from sub-groups (breast cancer stage, treatment type and time post-treatment) lacked concordance. Twenty-eight types of PROM were used: the EORTC QLQ-C30 was most common (50.6 %), followed by the SF-36 (32.3 %). There were 145 terms/labels for physical functioning: 'physical functioning/function' was used most often (82.3 %).

CONCLUSIONS

Findings point towards an older age and comorbidities being associated with more physical functioning declines. However, it was not possible to determine if stage, treatment type and time since treatment had any influence. More consistent use of the terminology 'physical functioning/function' would aid future comparisons of study results.

Multisensory System for Long-Term Activity Monitoring to Facilitate Aging-in-Place

Demographic changes and an ageing population require more effective methods to confront the increased prevalence of chronic diseases which generate dependence in older adults as well as an important rise in social expenditure. The challenge is not only to increase life expectancy, but also to ensure that the older adults can fully enjoy that moment in their lives, living where they wish to (private home, nursing home, …). Physical activity (PA) is a representative parameter of a person's state of health, especially when we are getting older, because it plays an important role in the prevention of diseases, and that is the reason why it is promoted in older adults. One of the goals of this work is to assess the feasibility of objectively measuring the PA levels of older adults wherever they live. In addition, this work proposes long-term monitoring that helps to gather daily activity patterns. We fuse inertial measurements with other technologies (WiFi- and ultrasonic-based location) in order to provide not only PA, but also information about the place where the activities are carried out, including both room-level location and precise positioning (depending on the technology used). With this information, we would be able to generate information about the person's daily routines which can be very useful for the early detection of physical or cognitive impairment.

Timed up-and-go performance is associated with objectively measured life space in patients 3 months after ischemic stroke: a cross-sectional observational study

BACKGROUND

Stroke is a common cause of mobility limitation, including a reduction in life space. Life space is defined as the spatial extent in which a person moves within a specified period of time. We aimed to analyze patients' objective and self-reported life space and clinical stroke characteristics.

METHODS

MOBITEC-Stroke is a prospective observational cohort study addressing poststroke mobility. This cross-sectional analysis refers to 3-month data. Life space was assessed by a portable tracking device (7 consecutive days) and by self-report (Life-Space Assessment; LSA). We analysed the timed up-and-go (TUG) test, stroke severity (National Institutes of Health Stroke Scale; NIHSS), and the level of functional outcome (modified Rankin Scale; mRS) in relation to participants' objective (distance- and area-related life-space parameters) and self-reported (LSA) life space by multivariable linear regression analyses, adjusted for age, sex, and residential area.

RESULTS

We included 41 patients, mean age 70.7 (SD11.0) years, 29.3% female, NIHSS score 1.76 (SD1.68). We found a positive relationship between TUG performance and maximum distance from home (p = 0.006), convex hull area (i.e. area enclosing all Global Navigation Satellite System [GNSS] fixes, represented as a polygon linking the outermost points; p = 0.009), perimeter of the convex hull area (i.e. total length of the boundary of the convex hull area; p = 0.008), as well as the standard ellipse area (i.e. the two-dimensional ellipse containing approximately 63% of GNSS points; p = 0.023), in multivariable regression analyses.

CONCLUSION

The TUG, an easily applicable bedside test, seems to be a useful indicator for patients' life space 3 months poststroke and may be a clinically useful measure to document the motor rehabilitative process.

Consumer wearable device-based measures of physical activity and energy expenditure in community-dwelling older adults with different levels of frailty: A STROBE compliant study

Physical activity is important for positive health outcomes, and wearable activity devices are useful for tracking physical activity patterns and energy expenditure. This study investigated differences in, and correlations of, duration of physical activity according to activity intensity and energy expenditure among community-dwelling older adults with different levels of frailty. This cross-sectional study enrolled 88 adults older than 65 years from communities between June 2019 and January 2020. The participants were divided into non-frail, pre-frail, and frail groups according to the frailty criteria. Outcomes included the frailty score, duration of physical activity according to the intensity of activity (sedentary, light, fairly active, fairly to very active, and very active), and energy expenditure measured by a consumer wearable device. The duration of physical activity according to the intensity of activity and energy expenditure were compared among non-frail, pre-frail, and frail groups. In addition, linear correlation analysis was used to identify significant associations of objectively measured physical activity and energy expenditure with frailty. Non-frail older adults showed significantly longer daily duration of light to very active physical activity and increased energy expenditure compared to the frail group (P < .05). Additionally, non-frail older adults engaged in significantly more light and fairly to very active physical activity, and showed increased energy expenditure, compared to the pre-frail group (P < .05). The non-frail group showed a significantly lower duration of sedentary behavior compared to the pre-frail group. Correlation analysis showed that frailty was significantly associated with decreased light to very active physical activity and energy expenditure, as well as increased sedentary behavior (P < .05). This study provides evidence of differences in objectively measured physical activity and energy expenditure between frail and non-frail older adults, and reveals an association of frailty with physical activity and energy expenditure. Daily physical activity that exceeds low-intensity, low-energy expenditure activity should be encouraged among older adults with frailty.

Gait monitoring for older adults during guided walking: An integrated assistive robot and wearable sensor approach

An active lifestyle can mitigate physical decline and cognitive impairment in older adults. Regular walking exercises for older individuals result in enhanced balance and reduced risk of falling. In this article, we present a study on gait monitoring for older adults during walking using an integrated system encompassing an assistive robot and wearable sensors. The system fuses data from the robot onboard Red Green Blue plus Depth (RGB-D) sensor with inertial and pressure sensors embedded in shoe insoles, and estimates spatiotemporal gait parameters and dynamic margin of stability in real-time. Data collected with 24 participants at a community center reveal associations between gait parameters, physical performance (evaluated with the Short Physical Performance Battery), and cognitive ability (measured with the Montreal Cognitive Assessment). The results validate the feasibility of using such a portable system in out-of-the-lab conditions and will be helpful for designing future technology-enhanced exercise interventions to improve balance, mobility, and strength and potentially reduce falls in older adults.

The Accuracy of Commercially Available Fitness Trackers in Patients after Stroke

Background: Fitness trackers could represent an easy-to-use and cheap tool for continuous tracking of physical activity of stroke survivors during the period of their recovery at home. The aim of the study was to examine the accuracy of the Fitbit activity tracker in locomotor activity monitoring of stroke survivors with respect to gait disorders, walking speed, walking aid, and placement of the tracker on body. Methods: Twenty-four ambulatory stroke survivors (15 men and 9 women) with locomotion/gait disorder were involved in the study. Patients underwent two walking tests with the Fitbit Alta HR trackers attached on 5 different places on body. The accuracy of the trackers has been analyzed on 3 groups of patients-those walking without any walking aid, those using a single-point stick and those using a rolling walker. Results: For no-aid patients, the most accurate place was the waist. Patients with a single-point stick revealed the smallest deviations for a tracker attached to a healthy lower limb, and patients with a rolling walker revealed the smallest deviations for a tracker attached on the paretic lower limb. Conclusions: An accuracy comparable with the healthy population can be reached for all of the three groups of patients, while fulfilling the conditions for minimum speed of 2 km/h and optimal placement of the trackers with respect to a walking aid and aspect to impairment.

Facilitators and barriers to real-life mobility in community-dwelling older adults: a narrative review of accelerometry- and global positioning system-based studies

Real-life mobility, also called "enacted" mobility, characterizes an individual's activity and participation in the community. Real-life mobility may be facilitated or hindered by a variety of factors, such as physical abilities, cognitive function, psychosocial aspects, and external environment characteristics. Advances in technology have allowed for objective quantification of real-life mobility using wearable sensors, specifically, accelerometry and global positioning systems (GPSs). In this review article, first, we summarize the common mobility measures extracted from accelerometry and GPS. Second, we summarize studies assessing the associations of facilitators and barriers influencing mobility of community-dwelling older adults with mobility measures from sensor technology. We found the most used accelerometry measures focus on the duration and intensity of activity in daily life. Gait quality measures, e.g., cadence, variability, and symmetry, are not usually included. GPS has been used to investigate mobility behavior, such as spatial and temporal measures of path traveled, location nodes traversed, and mode of transportation. Factors of note that facilitate/hinder community mobility were cognition and psychosocial influences. Fewer studies have included the influence of external environments, such as sidewalk quality, and socio-economic status in defining enacted mobility. Increasing our understanding of the facilitators and barriers to enacted mobility can inform wearable technology-enabled interventions targeted at delaying mobility-related disability and improving participation of older adults in the community.

Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review

Recent years have seen significant advances in the sensing capabilities of smartphones, enabling them to collect rich contextual information such as location, device usage, and human activity at a given point in time. Combined with widespread user adoption and the ability to gather user data remotely, smartphone-based sensing has become an appealing choice for health research. Numerous studies over the years have demonstrated the promise of using smartphone-based sensing to monitor a range of health conditions, particularly mental health conditions. However, as research is progressing to develop the predictive capabilities of smartphones, it becomes even more crucial to fully understand the capabilities and limitations of using this technology, given its potential impact on human health. To this end, this paper presents a narrative review of smartphone-sensing literature from the past 5 years, to highlight the opportunities and challenges of this approach in healthcare. It provides an overview of the type of health conditions studied, the types of data collected, tools used, and the challenges encountered in using smartphones for healthcare studies, which aims to serve as a guide for researchers wishing to embark on similar research in the future. Our findings highlight the predominance of mental health studies, discuss the opportunities of using standardized sensing approaches and machine-learning advancements, and present the trends of smartphone sensing in healthcare over the years.

Development of a measurement setup to detect the level of physical activity and social distancing of ageing people in a social garden during COVID-19 pandemic

This study defines a methodology to measure physical activity (PA) in ageing people working in a social garden while maintaining social distancing (SD) during COVID-19 pandemic. A real-time location system (RTLS) with embedded inertial measurement unit (IMU) sensors is used for measuring PA and SD. The position of each person is tracked to assess their SD, finding that the RTLS/IMU can measure the time in which interpersonal distance is not kept with a maximum uncertainty of 1.54 min, which compared to the 15-min. limit suggested to reduce risk of transmission at less than 1.5 m, proves the feasibility of the measurement. The data collected by the accelerometers of the IMU sensors are filtered using discrete wavelet transform and used to measure the PA in ageing people with an uncertainty-based thresholding method. PA and SD time measurements were demonstrated exploiting the experimental test in a pilot case with real users.

Development of the Digital Assessment of Precise Physical Activity (DAPPA) Tool for Older Adults

Physical activity (PA) is central to maintaining health and wellbeing as we age. Valid, reliable measurement tools are vital for understanding, and evaluating PA. There are limited options for comprehensively, accurately and affordably measuring older adults’ PA at scale at present. We aimed to develop a digital PA measurement tool specifically for adults aged 65+ using a person-based approach. We collated evidence from target users, field experts and the relevant literature to learn how older adults comprehend PA and would accept a digital tool. Findings suggest that older adults’ PA is often integrated into their daily life activities and that commonly applied terminology (e.g., moderate and vigorous) can be difficult to interpret. We also found that there is increasing familiarity with digital platforms amongst older adults, and that technological simplicity is valued. These findings informed the development of a digital tool that asks users to report their activities across key PA domains and dimensions from the previous 7-days. Users found the tool easy to navigate and comprehensive in terms of activity reporting. However, real-world usability testing revealed that users struggled with seven-day recall. Further work will address the identified issues, including creating a single-day reporting option, before commencing work to validate this new tool.

A Genetic Attack Against Machine Learning Classifiers to Steal Biometric Actigraphy Profiles from Health Related Sensor Data

In this work, we propose the use of a genetic-algorithm-based attack against machine learning classifiers with the aim of 'stealing' users' biometric actigraphy profiles from health related sensor data. The target classification model uses daily actigraphy patterns for user identification. The biometric profiles are modeled as what we call impersonator examples which are generated based solely on the predictions' confidence score by repeatedly querying the target classifier. We conducted experiments in a black-box setting on a public dataset that contains actigraphy profiles from 55 individuals. The data consists of daily motion patterns recorded with an actigraphy device. These patterns can be used as biometric profiles to identify each individual. Our attack was able to generate examples capable of impersonating a target user with a success rate of 94.5%. Furthermore, we found that the impersonator examples have high transferability to other classifiers trained with the same training set. We also show that the generated biometric profiles have a close resemblance to the ground truth profiles which can lead to sensitive data exposure, like revealing the time of the day an individual wakes-up and goes to bed.

Trends in Persuasive Technologies for Physical Activity and Sedentary Behavior: A Systematic Review

Persuasive technology (PT) is increasingly being used in the health and wellness domain to motivate and assist users with different lifestyles and behavioral health issues to change their attitudes and/or behaviors. There is growing evidence that PT can be effective at promoting behaviors in many health and wellness domains, including promoting physical activity (PA), healthy eating, and reducing sedentary behavior (SB). SB has been shown to pose a risk to overall health. Thus, reducing SB and increasing PA have been the focus of much PT work. This paper aims to provide a systematic review of PTs for promoting PA and reducing SB. Specifically, we answer some fundamental questions regarding its design and effectiveness based on an empirical review of the literature on PTs for promoting PA and discouraging SB, from 2003 to 2019 (170 papers). There are three main objectives: (1) to evaluate the effectiveness of PT in promoting PA and reducing SB; (2) to summarize and highlight trends in the outcomes such as system design, research methods, persuasive strategies employed and their implementaions, behavioral theories, and employed technological platforms; (3) to reveal the pitfalls and gaps in the present literature that can be leveraged and used to inform future research on designing PT for PA and SB.

Quantifying Habitual Physical Activity and Sedentariness in Older Adults-Different Outcomes of Two Simultaneously Body-Worn Motion Sensor Approaches and a Self-Estimation

Applicable and accurate assessment methods are required for a clinically relevant quantification of habitual physical activity (PA) levels and sedentariness in older adults. The aim of this study is to compare habitual PA and sedentariness, as assessed with (1) a wrist-worn actigraph, (2) a hybrid motion sensor attached to the lower back, and (3) a self-estimation based on a questionnaire. Over the course of one week, PA of 58 community-dwelling subjectively healthy older adults was recorded. The results indicate that actigraphy overestimates the PA levels in older adults, whereas sedentariness is underestimated when compared to the hybrid motion sensor approach. Significantly longer durations (hh:mm/day) for all PA intensities were assessed with the actigraph (light: 04:19; moderate to vigorous: 05:08) when compared to the durations (hh:mm/day) that were assessed with the hybrid motion sensor (light: 01:24; moderate to vigorous: 02:21) and the self-estimated durations (hh:mm/day) (light: 02:33; moderate to vigorous: 03:04). Actigraphy-assessed durations of sedentariness (14:32 hh:mm/day) were significantly shorter when compared to the durations assessed with the hybrid motion sensor (20:15 hh:mm/day). Self-estimated duration of light intensity was significantly shorter when compared to the results of the hybrid motion sensor. The results of the present study highlight the importance of an accurate quantification of habitual PA levels and sedentariness in older adults. The use of hybrid motion sensors can offer important insights into the PA levels and PA types (e.g., sitting, lying) and it can increase the knowledge about mobility-related PA and patterns of sedentariness, while actigraphy appears to be not recommendable for this purpose.

Monitoring ocular discomfort using a wrist-mounted electronic logger

PURPOSE

To investigate ocular discomfort during contact lens wear using a wrist-mounted electronic 'lens awareness logger' (LAL).

METHODS

Thirty symptomatic contact lens wearers wore study contact lenses for three days. On the first two days, two lens types which are known to differ in end-of-day comfort (lens A: senofilcon A and lens B: balafilcon A), were worn as a matching pair (randomised order). On day three, a pair of lens B was worn. On each day, the participant used a LAL. On day one and two, the participant pressed a button on the LAL whenever they became aware of their lenses due to discomfort. On day three, the participant used a multiple click protocol (1 = mild awareness to 3 = severe awareness) to report discomfort.

RESULTS

LAL events were similar on days one and two (17.3 vs. 15.8 events per day). There were significantly more LAL events for lens B (21.6 events per day) in comparison with lens A (11.6 events per day) (p = 0.006). The LAL event profile highlighted peaks in awareness following lens application and towards the end of the wearing cycle. Comparison of the LAL event profile for the two lens types showed significant differences in lens awareness, particularly in the first half of the wearing cycle. LAL events on day 3, showed a uniform distribution of single and double clicks through the day, but a marked peak in triple clicks in the last two hours of lens wear.

CONCLUSION

The LAL was able to differentiate between the study lenses and demonstrated differences in their LAL event profiles. Lens awareness associated with discomfort appeared to increase not only in frequency, but also in intensity towards the end of the wearing cycle. The ability of the LAL to track lens awareness suggests it is likely to be a useful tool in furthering understanding of ocular discomfort.