Wearable systems for monitoring mobility-related activities in older people: a systematic review

Effects of physiotherapy and home-based training in parkinsonian syndromes: protocol for a randomised controlled trial (MobilityAPP)

INTRODUCTION

Gait and mobility impairment are pivotal signs of parkinsonism, and they are particularly severe in atypical parkinsonian disorders including multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). A pilot study demonstrated a significant improvement of gait in patients with MSA of parkinsonian type (MSA-P) after physiotherapy and matching home-based exercise, as reflected by sensor-based gait parameters. In this study, we aim to investigate whether a gait-focused physiotherapy (GPT) and matching home-based exercise lead to a greater improvement of gait performance compared with a standard physiotherapy/home-based exercise programme (standard physiotherapy, SPT).

METHODS AND ANALYSIS

This protocol was deployed to evaluate the effects of a GPT versus an active control undergoing SPT and matching home-based exercise with regard to laboratory gait parameters, physical activity measures and clinical scales in patients with Parkinson's disease (PD), MSA-P and PSP. The primary outcomes of the trial are sensor-based laboratory gait parameters, while the secondary outcome measures comprise real-world derived parameters, clinical rating scales and patient questionnaires. We aim to enrol 48 patients per disease group into this double-blind, randomised-controlled trial. The study starts with a 1 week wearable sensor-based monitoring of physical activity. After randomisation, patients undergo a 2 week daily inpatient physiotherapy, followed by 5 week matching unsupervised home-based training. A 1 week physical activity monitoring is repeated during the last week of intervention.

ETHICS AND DISSEMINATION

This study, registered as 'Mobility in Atypical Parkinsonism: a Trial of Physiotherapy (Mobility_APP)' at clinicaltrials.gov (NCT04608604), received ethics approval by local committees of the involved centres. The patient's recruitment takes place at the Movement Disorders Units of Innsbruck (Austria), Erlangen (Germany), Lausanne (Switzerland), Luxembourg (Luxembourg) and Bolzano (Italy). The data resulting from this project will be submitted to peer-reviewed journals, presented at international congresses and made publicly available at the end of the trial.

TRIAL REGISTRATION NUMBER

NCT04608604.

Patient-perceived factors influencing physical activity sensor use in stroke prevention and rehabilitation: A thematic synthesis protocol

INTRODUCTION

While the putative benefits of "fitness trackers" continue to fuel a booming consumer market, results of device-based clinical interventions remain remarkably mixed. This study will explore factors influencing wearable physical activity (PA) sensor use in the context of stroke prevention and rehabilitation for older adults. The findings of this thematic synthesis will provide insights into factors influencing the use of PA sensors in stroke which may inform more effective device-based interventions.

METHODS AND ANALYSIS

Thematic synthesis as a formal method described by Thomas and Arden can be used within a systematic review to synthesize primary qualitative research. Accordingly, the proposed study will systematically search bibliographic databases for relevant peer-reviewed papers and synthesize coded thematic data within included papers. The quality of papers will be assessed using the JBI Critical Appraisal Checklist for Qualitative Research. Patterns in the text will be coded, preliminary data visualised, and higher-level analytical themes discerned to explain factors influencing the use of PA sensors in older stroke patients.

DISCUSSION

This study does not require ethics approval. Results are expected to be available by June 2024. Data from the thematic synthesis will provide insights into barriers and facilitators influencing the use of wearable PA sensors in stroke and older adults at risk, and implications these factors have for the design of effective device-based interventions.

TRIAL REGISTRATION

Systematic review registration: PROSPERO registration number: CRD42020211472. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020211472.

Real-world data capture of daily limb loading using force-sensing insoles: Feasibility and lessons learned

Force-sensing insoles are wearable technology that offer an innovative way to measure loading outside of laboratory settings. Few studies, however, have utilized insoles to measure daily loading in real-world settings. This is an ancillary study of a randomized controlled trial examining the effect of weight loss alone, weight loss plus weighted vest, or weight loss plus resistance training on bone health in older adults. The purpose of this ancillary study was to determine the feasibility of using force-sensing insoles to collect daily limb loading metrics, including peak force, impulse, and loading rate. Forty-four participants completed a baseline visit of three, 2-minute walking trials while wearing force-sensing insoles. During month two of the intervention, 37 participants wore insoles for 4 days for 8 waking hours each day. At 6-month follow-up, participants completed three, two-minute walking trials and a satisfaction questionnaire. Criteria for success in feasibility was defined as: a) > 60 % recruitment rate; b) > 80 % adherence rate; c) > 75 % of usable data, and d) > 75 % participant satisfaction. A 77.3 % recruitment rate was achieved, with 44 participants enrolled. Participants wore their insoles an average of 7.4 hours per day, and insoles recorded an average of 5.5 hours per day. Peak force, impulse, and loading rate collected at baseline and follow-up were 100 % usable. During the real-world settings, 87.8 % of data was deemed usable with an average of 1200 min/participant. Lastly, average satisfaction was 80.5 %. These results suggest that force-sensing insoles appears to be feasible to capture real-world limb loading in older adults.

Obesity-Specific Considerations for Assessing Gait with Inertial Measurement Unit-Based vs. Optokinetic Motion Capture

Adults with obesity experience high rates of disability and rapid functional decline. Identifying movement dysfunction early can direct intervention and disrupt disability development; however, subtle changes in movement are difficult to detect with the naked eye. This study evaluated how a portable, inertial measurement unit (IMU)-based motion capture system compares to a laboratory-based optokinetic motion capture (OMC) system for evaluating gait kinematics in adults with obesity. Ten adults with obesity performed overground walking while equipped with the OMC and IMU systems. Fifteen gait cycles for each participant were extracted for the 150 total cycles analyzed. Kinematics were compared between OMC and IMU across the gait cycles (coefficient of multiple correlations), at clinically significant time points (interclass correlations), and over clinically relevant ranges (Bland-Altman plots). Sagittal plane kinematics were most similar between systems, especially at the knee. Sagittal plane joint angles at clinically meaningful timepoints were poorly associated except for ankle dorsiflexion at heel strike (ρ = 0.38) and minimum angle (ρ = 0.83). All motions except for ankle dorsiflexion and hip abduction had >5° difference between systems across the range of angles measured. While IMU-based motion capture shows promise for detecting subtle gait changes in adults with obesity, more work is needed before this method can replace traditional OMC. Future work should explore standardization procedures to improve consistency of IMU motion capture performance.

Wearable technology use in long-term care facilities for older adults: a scoping review protocol

OBJECTIVE

The objective of this scoping review is to explore how wearable technology is being used to care for older adults in long-term care facilities.

INTRODUCTION

The use of digital health technologies to support care delivery in long-term care facilities for older adults has grown significantly in recent years, especially since the COVID-19 pandemic. Wearable technology refers to devices worn or attached to the body that can track a variety of health-related data, such as vital signs, falls, and sleep patterns. Despite the evidence that wearable devices are playing an increasing role in older adults' care, no review has been conducted on how wearable technology is being used in long-term care facilities.

INCLUSION CRITERIA

This review will consider studies that include people aged over 65, with any health condition or level of disability, who live in long-term care facilities. Primary and secondary studies using quantitative, qualitative, and mixed methods study designs will be included. Dissertations and policy documents will also be considered.

METHODS

Data sources will include comprehensive searches of electronic databases (MEDLINE, Embase, CINAHL, and Scopus), gray literature, and reference scanning of relevant studies. Two independent reviewers will screen titles, abstracts, and full texts of the selected studies. Data extraction will be performed using a tool developed by the researchers. Data will be mapped and analyzed. Descriptive frequencies and content analysis will be included, along with the tabulated results, which will be used to present the findings with regard to the review objectives.

REVIEW REGISTRATION

Open Science Framework https://osf.io/r9qtd.

Harnessing physical activity monitoring and digital biomarkers of frailty from pendant based wearables to predict chemotherapy resilience in veterans with cancer

This study evaluated the use of pendant-based wearables for monitoring digital biomarkers of frailty in predicting chemotherapy resilience among 27 veteran cancer patients (average age: 64.6 ± 13.4 years), undergoing bi-weekly chemotherapy. Immediately following their first day of chemotherapy cycle, participants wore a water-resistant pendant sensor for 14 days. This device tracked frailty markers like cadence (slowness), daily steps (inactivity), postural transitions (weakness), and metrics such as longest walk duration and energy expenditure (exhaustion). Participants were divided into resilient and non-resilient groups based on adverse events within 6 months post-chemotherapy, including dose reduction, treatment discontinuation, unplanned hospitalization, or death. A Chemotherapy-Resilience-Index (CRI) ranging from 0 to 1, where higher values indicate poorer resilience, was developed using regression analysis. It combined physical activity data with baseline Eastern Cooperative Oncology Group (ECOG) assessments. The protocol showed a 97% feasibility rate, with sensor metrics effectively differentiating between groups as early as day 6 post-therapy. The CRI, calculated using data up to day 6 and baseline ECOG, significantly distinguished resilient (CRI = 0.2 ± 0.27) from non-resilient (CRI = 0.7 ± 0.26) groups (p < 0.001, Cohen's d = 1.67). This confirms the potential of remote monitoring systems in tracking post-chemotherapy functional capacity changes and aiding early non-resilience detection, subject to validation in larger studies.

A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings

Walking activity and gait parameters are considered among the most relevant mobility-related parameters. Currently, gait assessments have been mainly analyzed in laboratory or hospital settings, which only partially reflect usual performance (i.e., real world behavior). In this study, we aim to validate a robust walking detection algorithm using a single foot-worn inertial measurement unit (IMU) in real-life settings. We used a challenging dataset including 18 individuals performing free-living activities. A multi-sensor wearable system including pressure insoles, multiple IMUs, and infrared distance sensors (INDIP) was used as reference. Accurate walking detection was obtained, with sensitivity and specificity of 98 and 91% respectively. As robust walking detection is needed for ambulatory monitoring to complete the processing pipeline from raw recorded data to walking/mobility outcomes, a validated algorithm would pave the way for assessing patient performance and gait quality in real-world conditions.

The Use of Wearable Technologies in the Assessment of Physical Activity in Preschool- and School-Age Youth: Systematic Review

In recent years, physical activity assessment has increasingly relied on wearable monitors to provide measures for surveillance, intervention, and epidemiological research. This present systematic review aimed to examine the current research about the utilization of wearable technology in the evaluation in physical activities of preschool- and school-age children. A database search (Web of Science, PubMed and Scopus) for original research articles was performed. A total of twenty-one articles met the inclusion criteria, and the Cochrane risk of bias tool was used. Wearable technology can actually be a very important instrument/tool to detect the movements and monitor the physical activity of children and adolescents. The results revealed that there are a few studies on the influence of these technologies on physical activity in schools, and most of them are descriptive. In line with previous research, the wearable devices can be used as a motivational tool to improve PA behaviors and in the evaluation of PA interventions. However, the different reliability levels of the different devices used in the studies can compromise the analysis and understanding of the results.

Unlocking the black box of geriatric physiotherapy : Quantification of physical activity and walking parameters during inpatient geriatric rehabilitation therapy sessions

BACKGROUND

Physiotherapy and occupational therapy are currently described using the duration of treatment (days or weeks), the frequency of therapy sessions (on a daily or 3-5 days per week basis) and considering the duration of a session (e.g., 30 or 45 min). The content is often poorly defined and the intensity is rarely reported. Using digital technology some of these shortcomings can be overcome. The cumulative parameters of walking and activity sessions, the duration of walking, the time spent in an upright or lying/sitting position and the number of steps can now be analyzed. In this study, we examined the parameters during non-treatment periods and therapy time in patients recovering from fragility fractures.

METHODS

The study is a secondary data analysis of a trial that examined the improvement of physical activity (PA) and self-efficacy of fragility fracture patients. Changes in mobility parameters were measured using the ActivPal3 sensor during the 1st and 3rd weeks of rehabilitation and 104 patients were analyzed (mean age 82.5 years). Parameters included the time during supervised treatment, the mean number of steps, cumulative time in an upright position and walking duration, the number of walking intervals of > 10 s and sit to stand transfers.

RESULTS

Patients received 3-4 therapy sessions adding up to 90-120 min per day. More than 50% of the daily walking activities were achieved in these sessions until discharge. With this amount of therapeutic input most parameters meaningfully improved from baseline to the second measurement. The number of steps increased by 30%, the mean time in an upright position increased by 26% and the mean time spent walking increased by 49%.

CONCLUSION

The sensor-derived measurements describe the amount of walking activity administered during the supervised therapy sessions. This could be used as a starting point for future trials to improve the outcomes or as a standard of process evaluation for clinical services.

Inertial measurement unit-based motion capture to replace camera-based systems for assessing gait in healthy young adults: Proceed with caution

Gait analysis can identify injury-risk markers indiscernible to the naked eye. Inertial measurement unit (IMU)-based motion capture circumvents optokinetic motion capture (OMC) clinical implementation barriers with its portability, increased affordability, and decreased computational burden. We compared an IMU system to a robust OMC marker set for gait analysis. 10 healthy adults walked at self-selected speeds equipped with Noraxon MyoMotion IMUs and a 24-marker, 5-cluster marker-set in view of 14 OMC cameras. A single calibration was applied. IMU system and OMC calculated joint angles were compared. A single calibration performed similarly to previously reported repeated calibration. IMU and OMC agreement was best in the sagittal plane with IMU axis-mixing affecting off-sagittal plane agreement. System differences were greater than 5° for most motions. Measurement system bias showed at the ankle and knee, however differences varied across participants. IMU kinematics should be interpreted with caution; consistency and accuracy must improve before IMUs can replace OMC.

How Long Should GPS Recording Lengths Be to Capture the Community Mobility of An Older Clinical Population? A Parkinson's Example

Wearable global position system (GPS) technology can help those working with older populations and people living with movement disorders monitor and maintain their mobility level. Health research using GPS often employs inconsistent recording lengths due to the lack of a standard minimum GPS recording length for a clinical context. Our work aimed to recommend a GPS recording length for an older clinical population. Over 14 days, 70 older adults with Parkinson's disease wore the wireless inertial motion unit with GPS (WIMU-GPS) during waking hours to capture daily "time outside", "trip count", "hotspots count" and "area size travelled". The longest recording length accounting for weekend and weekdays was ≥7 days of ≥800 daily minutes of data (14 participants with 156, 483.9 min recorded). We compared the error rate generated when using data based on recording lengths shorter than this sample. The smallest percentage errors were observed across all outcomes, except "hotspots count", with daily recordings ≥500 min (8.3 h). Eight recording days will capture mobility variability throughout days of the week. This study adds empirical evidence to the sensor literature on the required minimum duration of GPS recording.

Objective and Self-reported Assessment of Physical Activity of Women over 60 Years Old

The aim of the study was to examine changes in objective and self-reported physical activity (PA) among women aged 60 years and older. The study included 200 women aged over 60 years, divided into three groups according to age (60–65 years, 66–70 years, > 70 years). The subjective assessment was provided with the International Physical Activity Questionnaire (IPAQ) – short version with self-reported PA assessment, and objective data was provided by an Actigraph GT3-BT worn for seven days. Significant differences in moderate and high intensity PA, moderate-to-vigorous PA and steps per day were found between the oldest and youngest groups; as well as in low, moderate, moderate-to-vigorous PA and steps per day between groups middle and oldest. In all three age groups, 1) significant differences were observed between subjective and objective measurements of physical activity and 2) no correlation was found between assessment measures. It was found that only direct PA measurement declined with age in women over 60 years old, and that sedentary behavior is underestimated, and moderate and vigorous PA overestimated, with the self-reported IPAQ.

Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping

Increased levels of light, moderate and vigorous physical activity (PA) are positively associated with health benefits. Therefore, sensor-based human activity recognition can identify different types and levels of PA. In this paper, we propose a two-layer locomotion recognition method using dynamic time warping applied to inertial sensor data. Based on a video-validated dataset (ADAPT), which included inertial sensor data recorded at the lower back (L5 position) during an unsupervised task-based free-living protocol, the recognition algorithm was developed, validated and tested. As a first step, we focused on the identification of locomotion activities walking, ascending and descending stairs. These activities are difficult to differentiate due to a high similarity. The results showed that walking could be recognized with a sensitivity of 88% and a specificity of 89%. Specificity for stair climbing was higher compared to walking, but sensitivity was noticeably decreased. In most cases of misclassification, stair climbing was falsely detected as walking, with only 0.2–5% not assigned to any of the chosen types of locomotion. Our results demonstrate a promising approach to recognize and differentiate human locomotion within a variety of daily activities.

Internet of things (IoT) applications for elderly care: a reflective review

Increasing in elderly population put extra pressure on healthcare systems globally in terms of operational costs and resources. To minimize this pressure and provide efficient healthcare services, the application of the Internet of Things (IoT) and wearable technology could be promising. These technologies have the potential to improve the quality of life of the elderly population while reducing strain on healthcare systems and minimizing their operational cost. Although IoT and wearable applications for elderly healthcare purposes were reviewed previously, there is a further need to summarize their current applications in this fast-developing area. This paper provides a comprehensive overview of IoT and wearable technologies' applications including the types of data collected and the types of devices for elderly healthcare. This paper provides insights into existing areas of IoT/wearable applications while presenting new research opportunities in emerging areas of applications, such as robotic technology and integrated applications. The analysis in this paper could be useful to healthcare solution designers and developers in defining technology supported futuristic healthcare strategies to serve elderly people and increasing their quality of life.

Evaluation of Wearable Technology in Dementia: A Systematic Review and Meta-Analysis

Background: The objective of this analysis was to systematically review studies employing wearable technology in patients with dementia by quantifying differences in digitally captured physiological endpoints.

Methods: This systematic review and meta-analysis was based on web searches of Cochrane Database, PsycInfo, Pubmed, Embase, and IEEE between October 25–31st, 2017. Observational studies providing physiological data measured by wearable technology on participants with dementia with a mean age ≥50. Data were extracted according to PRISMA guidelines and methodological quality assessed independently using Downs and Black criteria. Standardized mean differences between cases and controls were estimated using random-effects models.

Results: Forty-eight studies from 18,456 screened abstracts (Dementia: n = 2,516, Control: n = 1,224) met inclusion criteria for the systematic review. Nineteen of these studies were included in one or multiple meta-analyses (Dementia: n = 617, Control: n = 406). Participants with dementia demonstrated lower levels of daily activity (standardized mean difference (SMD), −1.60; 95% CI, −2.66 to −0.55), decreased sleep efficiency (SMD, −0.52; 95% CI, −0.89 to −0.16), and greater intradaily circadian variability (SMD, 0.46; 95% CI, 0.27 to 0.65) than controls, among other measures. Statistical between-study heterogeneity was observed, possibly due to variation in testing duration, device type or patient setting.

Conclusions and Relevance: Digitally captured data using wearable devices revealed that adults with dementia were less active, demonstrated increased fragmentation of their sleep-wake cycle and a loss of typical diurnal variation in circadian rhythm as compared to controls.

Usefulness of Mobile Devices in the Diagnosis and Rehabilitation of Patients with Dizziness and Balance Disorders: A State of the Art Review

Objective

The gold standard for objective body posture examination is posturography. Body movements are detected through the use of force platforms that assess static and dynamic balance (conventional posturography). In recent years, new technologies like wearable sensors (mobile posturography) have been applied during complex dynamic activities to diagnose and rehabilitate balance disorders. They are used in healthy people, especially in the aging population, for detecting falls in the older adults, in the rehabilitation of different neurological, osteoarticular, and muscular system diseases, and in vestibular disorders. Mobile devices are portable, lightweight, and less expensive than conventional posturography. The vibrotactile system can consist of an accelerometer (linear acceleration measurement), gyroscopes (angular acceleration measurement), and magnetometers (heading measurement, relative to the Earth’s magnetic field). The sensors may be mounted to the trunk (most often in the lumbar region of the spine, and the pelvis), wrists, arms, sternum, feet, or shins. Some static and dynamic clinical tests have been performed with the use of wearable sensors. Smartphones are widely used as a mobile computing platform and to evaluate the results or monitor the patient during the movement and rehabilitation. There are various mobile applications for smartphone-based balance systems. Future research should focus on validating the sensitivity and reliability of mobile device measurements compared to conventional posturography.

Conclusion

Smartphone based mobile devices are limited to one sensor lumbar level posturography and offer basic clinical evaluation. Single or multi sensor mobile posturography is available from different manufacturers and offers single to multi-level measurements, providing more data and in some instances even performing sophisticated clinical balance tests.

Promotion of Physical Activity in Older People Using mHealth and eHealth Technologies: Rapid Review of Reviews

BACKGROUND

Older people are at increased risk of adverse health events because of reduced physical activity. There is concern that activity levels are further reduced in the context of the COVID-19 pandemic, as many older people are practicing physical and social distancing to minimize transmission. Mobile health (mHealth) and eHealth technologies may offer a means by which older people can engage in physical activity while physically distancing.

OBJECTIVE

The objective of this study was to assess the evidence for mHealth or eHealth technology in the promotion of physical activity among older people aged 50 years or older.

METHODS

We conducted a rapid review of reviews using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched for systematic reviews published in the English language in 3 electronic databases: MEDLINE, CINAHL Plus, and Scopus. Two reviewers used predefined inclusion criteria to select relevant reviews and extracted data on review characteristics and intervention effectiveness. Two independent raters assessed review quality using the AMSTAR-2 tool.

RESULTS

Titles and abstracts (n=472) were screened, and 14 full-text reviews were assessed for eligibility. Initially, we included 5 reviews but excluded 1 from the narrative as it was judged to be of critically low quality. Three reviews concluded that mHealth or eHealth interventions were effective in increasing physical activity. One review found that the evidence was inconclusive.

CONCLUSIONS

There is low to moderate evidence that interventions delivered via mHealth or eHealth approaches may be effective in increasing physical activity in older adults in the short term. Components of successful interventions include self-monitoring, incorporation of theory and behavior change techniques, and social and professional support.

Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults

The use of technology has been suggested as a means of allowing continued autonomous living for older adults, while reducing the burden on caregivers and aiding decision-making relating to healthcare. However, more clarity is needed relating to the Activities of Daily Living (ADL) recognised, and the types of technology included within current monitoring approaches. This review aims to identify these differences and highlight the current gaps in these systems. A scoping review was conducted in accordance with PRISMA-ScR, drawing on PubMed, Scopus, and Google Scholar. Articles and commercially available systems were selected if they focused on ADL recognition of older adults within their home environment. Thirty-nine ADL recognition systems were identified, nine of which were commercially available. One system incorporated environmental and wearable technology, two used only wearable technology, and 34 used only environmental technologies. Overall, 14 ADL were identified but there was variation in the specific ADL recognised by each system. Although the use of technology to monitor ADL of older adults is becoming more prevalent, there is a large variation in the ADL recognised, how ADL are defined, and the types of technology used within monitoring systems. Key stakeholders, such as older adults and healthcare workers, should be consulted in future work to ensure that future developments are functional and useable.

Evaluation of 1-Year in-Home Monitoring Technology by Home-Dwelling Older Adults, Family Caregivers, and Nurses

Introduction: Population aging is increasing the needs and costs of healthcare. Both frailty and the chronic diseases affecting older people reduce their ability to live independently. However, most older people prefer to age in their own homes. New development of in-home monitoring can play a role in staying independent, active, and healthy for older people. This 12-month observational study aimed to evaluate a new in-home monitoring system among home-dwelling older adults (OA), their family caregivers (FC), and nurses for the support of home care. Methods: The in-home monitoring system evaluated in this study continuously monitored OA's daily activities (e.g., mobility, sleep habits, fridge visits, door events) by ambient sensor system (DomoCare®) and health-related events by wearable sensors (Activity tracker, ECG). In the case of deviations in daily activities, alerts were transmitted to nurses via email. Using specific questionnaires, the opinions of 13 OA, 13 FC, and 20 nurses were collected at the end of 12-months follow-up focusing on user experience and the impact of in-home monitoring on home care services. Results: The majority of OA, FC, and nurses considered that in-home sensors can help with staying at home, improving home care and quality of life, preventing domestic accidents, and reducing family stress. The opinion tended to be more frequently favorable toward ambient sensors (76%; 95% CI: 61-87%) than toward wearable sensors (Activity tracker: 65%; 95% CI: 50-79%); ECG: 60%; 95% CI: 45-75%). On average, OA (74%; 95% CI: 46-95%) and FC (70%; 95% CI: 39-91%) tended to be more enthusiastic than nurses (60%; 95% CI: 36-81%). Some barriers reported by nurses were a fear of weakening of the relationship with OA and lack of time. Discussion/Conclusion: Overall, the opinions of OA, FC, and nurses were positively related to in-home sensors, with nurses being less enthusiastic about their use in clinical practice.

The Use of Inertial Measurement Units for the Study of Free Living Environment Activity Assessment: A Literature Review

This article presents an overview of fifty-eight articles dedicated to the evaluation of physical activity in free-living conditions using wearable motion sensors. This review provides a comprehensive summary of the technical aspects linked to sensors (types, number, body positions, and technical characteristics) as well as a deep discussion on the protocols implemented in free-living conditions (environment, duration, instructions, activities, and annotation). Finally, it presents a description and a comparison of the main algorithms and processing tools used for assessing physical activity from raw signals.

Application of Activity Trackers among Nursing Home Residents-A Pilot and Feasibility Study on Physical Activity Behavior, Usage Behavior, Acceptance, Usability and Motivational Impact

The aim of this study was to assess physical activity and sedentary behavior, as well as the usage behavior, usability, acceptance, and motivational impact of an applied activity tracker among nursing home residents. Physical activity and usage behavior were measured among 22 residents (68 to 102 years) by use of a commercial activity tracker worn during waking hours for 77 days on average. Usability, acceptance, and motivational impact of the tracker were examined using an adapted questionnaire. Participants walked, on average, 1007 ± 806 steps per day and spent, on average, more than 9 h (77.2% of their waking time) sedentary. The average steps/day increased significantly within the first five weeks of wearing the activity tracker. The acceptance rate was high (94.4%). The tracker was used for 65.4% of the individual study period, and usage behavior did not significantly change during the first five wearing weeks. Participants with a usage time of ≥50% walked significantly more steps per day than those with a lower usage. Overall, we were able to reveal that the residents were highly inactive and sedentary. The results support the feasibility of a long-term application of activity trackers to assess or even increase physical activity behavior.

Cancer Patients' Perception of Usefulness of Wearable Exercise Trackers

OBJECTIVE

To determine the feasibility and perception of usefulness of wearable trackers in inpatient and outpatient cancer rehabilitation patients.

DESIGN

Prospective study.

SETTING

Acute inpatient rehabilitation and outpatient clinic at a tertiary cancer center.

PARTICIPANTS

Adult cancer patients (N = 100).

INTERVENTIONS

Participants were provided with wearable trackers for the duration of the study.

MAIN OUTCOME MEASURES

Survey regarding feasibility (as defined as equal or more than two-thirds of participants reporting use of the wearable tracker) and usefulness of the wearable tracker and Edmonton Symptom Assessment Scale (ESAS-FS) in both inpatient and outpatient populations. Activity minutes, number of steps, heart rate, and sleep data were collected from the wearable tracker.

RESULTS

Patients reported the use of a wearable tracker is feasible, with 48/50 (96%) outpatients and 47/50 (94%) inpatients reported wearing the wearable tracker daily and 37/49 (76%) outpatients and 29/50 (58%) inpatients reported that they would continue to wear the wearable tracker after this study. The majority of cancer patients (41/49 [84%] of outpatient and 33/50 [66%] of inpatient patients) reported that the wearable tracker was useful and 41/49 (84%) outpatients and 27/50 (54%) inpatients perceived the wearable tracker as helping to increase physical activity.

CONCLUSIONS

The use of wearable trackers in cancer patients is feasible and patients perceive wearable trackers as useful in both the inpatient and outpatient rehabilitation setting. Physical activity in these patients was better in the outpatient population, as expected because of less medical acuity.

Concurrent validity and within-session reliability of gait kinematics measured using an inertial motion capture system with repeated calibration

INTRODUCTION

Wearable inertial measurement units (IMUs) enable gait analysis in the clinic, but require calibrations that may affect subsequent gait measurements. This study assessed concurrent validity and within-session reliability of gait kinematics measured by a frequently calibrated IMU-based system. Calibration pose accuracy and intra-rater repeatability, and IMU orientation tracking accuracy, were additionally quantified.

METHODS

Calibration poses and gait were recorded in 15 women using IMUs and optical motion capture (OMC) (reference standard) simultaneously. Participants performed six consecutive trials: each comprising a calibration pose and a walk. IMU tracking was assessed separately (once-off) using technical static and dynamic tests. Differences of > 5° constituted clinical significance.

RESULTS

Concurrent validity for gait revealed clinically significant between-system differences for sagittal angles (root-mean-square error [RMSE] 6.7°-15.0°; bias -9.3°-3.0°) and hip rotation (RMSE 7.9°; bias -4.2°). After removing modelling offsets, differences for all angles (except hip rotation) were < 5°. Gait curves correlated highly between systems (r > 0.8), except hip rotation, pelvic tilt and -obliquity. Within-session reliability of IMU-measured gait angles was clinically acceptable (standard error of measurement [SEM] < 5°). Calibration poses were repeatable (SEM 0.3°-2.2°). Pose accuracy revealed mean absolute differences (MAD) < 5° for all angles except sagittal ankle, hip and pelvis. IMU tracking accuracy demonstrated RMSE ≤ 2.0°.

CONCLUSION

A frequently calibrated IMU system provides reliable gait measurements; comparing highly to OMC after removing modelling differences. Calibration poses can be implemented accurately for most angles and consistently. IMU-measured gait data are clinically useful and comparable within participants, but should not be compared to OMC-measured data.

Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study

BACKGROUND

Falls are a common health problem, which in the worst cases can lead to death. To develop reliable fall detection algorithms as well as suitable prevention interventions, it is important to understand circumstances and characteristics of real-world fall events. Although falls are common, they are seldom observed, and reports are often biased. Wearable inertial sensors provide an objective approach to capture real-world fall signals. However, it is difficult to directly derive visualization and interpretation of body movements from the fall signals, and corresponding video data is rarely available.

OBJECTIVE

The re-enactment method uses available information from inertial sensors to simulate fall events, replicate the data, validate the simulation, and thereby enable a more precise description of the fall event. The aim of this paper is to describe this method and demonstrate the validity of the re-enactment approach.

METHODS

Real-world fall data, measured by inertial sensors attached to the lower back, were selected from the Fall Repository for the Design of Smart and Self-Adaptive Environments Prolonging Independent Living (FARSEEING) database. We focused on well-described fall events such as stumbling to be re-enacted under safe conditions in a laboratory setting. For the purposes of exemplification, we selected the acceleration signal of one fall event to establish a detailed simulation protocol based on identified postures and trunk movement sequences. The subsequent re-enactment experiments were recorded with comparable inertial sensor configurations as well as synchronized video cameras to analyze the movement behavior in detail. The re-enacted sensor signals were then compared with the real-world signals to adapt the protocol and repeat the re-enactment method if necessary. The similarity between the simulated and the real-world fall signals was analyzed with a dynamic time warping algorithm, which enables the comparison of two temporal sequences varying in speed and timing.

RESULTS

A fall example from the FARSEEING database was used to show the feasibility of producing a similar sensor signal with the re-enactment method. Although fall events were heterogeneous concerning chronological sequence and curve progression, it was possible to reproduce a good approximation of the motion of a person's center of mass during fall events based on the available sensor information.

CONCLUSIONS

Re-enactment is a promising method to understand and visualize the biomechanics of inertial sensor-recorded real-world falls when performed in a suitable setup, especially if video data is not available.

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.

Feasible but Not Yet Efficacious: A Scoping Review of Wearable Activity Monitors in Interventions Targeting Physical Activity, Sedentary Behavior, and Sleep

Purpose of Review

The present review aimed to explore the range and characteristics of interventions that utilize WAM and descriptively summarize the efficacy of these interventions.

Recent Findings

A total of 65 articles (61 studies) were included in this review. Most of the WAM-based interventions (n=58) were designed to improve physical activity (PA). Interventions targeting sedentary behavior (SB) were much less common (n=12), and even less frequent were WAM-based sleep interventions (n=3). Most studies tested the feasibility of WAM-based interventions; hence, efficacy of these interventions in improving PA, SB, and/or sleep could not be conclusively determined. Nonetheless, WAM-based interventions showed considerable potential in increasing PA and decreasing SB.

Summary

WAM-based PA interventions exhibited preliminary efficacy in increasing PA. Although not as many interventions were focused on SB, current interventions also showed potential in decreasing sedentary time. Meanwhile, more evidence is needed to determine the utility of WAM in improving sleep. Major challenges with including WAM as part of interventions are reduced engagement in using the devices over time and the rapid changes in technology resulting in devices becoming obsolete soon after completion of an efficacy trial.

Change of Objectively-Measured Physical Activity during Geriatric Rehabilitation

This prospective study investigated feasibility and sensitivity of sensor-based physical activity (PA) measures to monitor changes in PA during geriatric rehabilitation and its relation to clinical parameters at admission. PA was routinely measured at day 2 and day 15 after admission in 647 patients (70.2% women, mean age = 82.0 (SD = 7.19) years) of a German geriatric hospital using a thigh-worn accelerometer. Clinical records were used to include age, Barthel Index, diagnosis, mobility, orientation and cognition. Mean values and 95% confidence intervals (95%-CI) of walking duration, walking bout duration and number of sit-to-stand transfers were calculated to quantify different domains of PA. All observed PA parameters improved during rehabilitation, regardless of age, diagnosis or physical and cognitive function at admission. Walking duration increased by 12.1 (95%-CI: 10.3; 13.8) min, walking bout duration by 2.39 (95%-CI: 1.77; 3.00) s, and number of sit-to-stand transfers by 7 (95%-CI: 5; 8). Floor and ceiling effects were not observed. Walking duration at day 2 as well as day 15 was continuously associated with Barthel Index and statistically significant improved for all levels of Barthel Index. In summary, this study showed that sensor-based PA monitoring is feasible to assess the individual progress in geriatric rehabilitation patients.

Neurophysiological Effects of High Velocity and Low Amplitude Spinal Manipulation in Symptomatic and Asymptomatic Humans: A Systematic Literature Review

STUDY DESIGN

Systematic review.

OBJECTIVE

To summarize the evidence of neurophysiological effects of spinal manipulative therapy (SMT) with a high velocity low amplitude thrust (HVLA-SMT) in asymptomatic and symptomatic humans.

SUMMARY OF BACKGROUND DATA

HVLA-SMT is effective in reducing back pain, but its mode of action is not fully understood.

METHODS

A systematic literature search (until July 2018) was conducted by a professional librarian in seven databases (Medline (OvidSP), Premedline (PubMed), EMBASE, Cochrane, CINAHL, PEDro, and Scopus). Two authors selected the studies according to the a priori described criteria and scored study quality. Only controlled studies of at least moderate quality were included. Effects of HVLA-SMT on a particular outcome measure were defined as more than one study showing a significantly greater effect of HVLA-SMT compared with the control intervention.

RESULTS

From the 18 studies included (932 participants in total), there was evidence only for an association between HVLA-SMT and changes in the autonomic nervous system, reflected in changes in heart rate variability and skin conductance. Most studies focused on healthy volunteers and none related neurophysiologic changes to pain reduction.

CONCLUSION

This systematic review points to HVLA-SMT affecting the autonomic nervous system. The effects seem to depend on the spinal level of HVLA-SMT application and might differ between healthy volunteers and pain patients. There is a need for high-quality studies that include patients, well characterized for pain duration and outcome measure baseline values, and address the relation between changes in neurophysiology and pain.

LEVEL OF EVIDENCE

2.

A smart shoe insole to monitor frail older adults walking speed: results of two evaluation phases completed in a living-lab and through a 12-week pilot study (Preprint)

Background

Recent World Health Organization reports propose wearable devices to collect information on activity and walking speed as innovative health indicators. However, mainstream consumer-grade tracking devices and smartphone apps are often inaccurate and require long-term acceptability assessment.

Objective

Our aim is to assess the user acceptability of an instrumented shoe insole in frail older adults. This device monitors participants’ walking speed and differentiates active walking from shuffling after step length calibration.

Methods

A multiphase evaluation has been designed: 9 older adults were evaluated in a living lab for a day, 3 older adults were evaluated at home for a month, and a prospective randomized trial included 35 older adults at home for 3 months. A qualitative research design using face-to-face and phone semistructured interviews was performed. Our hypothesis was that this shoe insole was acceptable in monitoring long-term outdoor and indoor walking. The primary outcome was participants' acceptability, measured by a qualitative questionnaire and average time of insole wearing per day. The secondary outcome described physical frailty evolution in both groups.

Results

Living lab results confirmed the importance of a multiphase design study with participant involvement. Participants proposed insole modifications. Overall acceptability had mixed results: low scores for reliability (2.1 out of 6) and high scores for usability (4.3 out of 6) outcomes. The calibration phase raised no particular concern. During the field test, a majority of participants (mean age 79 years) were very (10/16) or quite satisfied (3/16) with the insole's comfort at the end of the follow-up. Participant insole acceptability evolved as follows: 63% (12/19) at 1 month, 50% (9/18) at 2 months, and 75% (12/16) at 3 months. A total of 9 participants in the intervention group discontinued the intervention because of technical issues. All participants equipped for more than a week reported wearing the insole every day at 1 month, 83% (15/18) at 2 months, and 94% (15/16) at 3 months for 5.8, 6.3, and 5.1 hours per day, respectively. Insole data confirmed that participants effectively wore the insole without significant decline during follow-up for an average of 13.5 days per 4 months and 5.6 hours per day. For secondary end points, the change in frailty parameters or quality of life did not differ for those randomly assigned to the intervention group compared to usual care.

Conclusions

Our study reports acceptability data on an instrumented insole in indoor and outdoor walking with remote monitoring in frail older adults under real-life conditions. To date, there is limited data in this population set. This thin instrumentation, including a flexible battery, was a technical challenge and seems to provide an acceptable solution over time that is valued by participants. However, users still raised certain acceptability issues. Given the growing interest in wearable health care devices, these results will be useful for future developments.

Trial Registration

ClinicalTrials.gov NCT02316600; https://clinicaltrials.gov/ct2/show/NCT02316600

Using smart garments to differentiate among normal and simulated abnormal gaits

Detecting and assessing an individual's gait can be important for medical diagnostic purposes and for developing and guiding follow-on rehabilitation protocols. Thus, an accurate, objective gait classification system has the potential to facilitate earlier diagnosis and improved clinical decision-making. Systems using smart garments represent an emerging technology for physical activity assessment and that may be relevant for gait classification. The objective of this study was to assess the accuracy of one such system - comprised of commercial instrumented socks and a custom instrument shirt - for differentiating among normal gait and four distinct simulated gait abnormalities. Eleven participants completed an experiment in which they completed several gait trails on a single day. Gait types were classified using diverse modeling approaches (K-nearest neighbors, linear discriminant analyses, support vector machines, and artificial neural networks). High classification accuracy could be obtained, both when classification models were developed and tested using data from each participant separately and grouped together, particularly using the k-nearest neighbor method (>98% accuracy). Some gaits were more often "confused" with other gaits, especially when they shared underlying kinematic aspects. These results support the potential of using "smart" garments for detecting and identifying abnormal gaits, and for future implementation in diagnosis and rehabilitation.

Gait characteristics of CKD patients: a systematic review

BACKGROUND

People with Chronic Kidney Disease (CKD) often present with prevalent gait impairment and high fall rates, particularly in advanced CKD stages. Gait impairment and its consequences is associated with increased hospital admission, institutionalization, and greater need for health care. The objective of this systematic review was to evaluate the quality of studies investigating CKD patients' gait characteristics at different CKD stages, to highlight areas of agreement and contradiction between studies reporting aspects of gait in CKD, and to discuss and emphasize gait parameters associated with fall risk.

METHODS

We performed a literature search of trials in CINAHL (EBSCO), Cochrane Library, EMBASE, Medline (EBSCO), PEDro, PubMed, and Scopus databases from their inception to June 30th 2018 using a two-stage process for the identification of studies. We retrieved English-, German-, Italian-, Spanish-, Portuguese and Dutch-language articles for review. Methodological quality of randomized and non-randomized studies was assessed with an adapted version of the Downs and Black checklist.

RESULTS

Thirty-one studies (22 cross-sectional with 3901 participants) and 9 longitudinal intervention studies (1 randomized control trial, 5 controlled clinical trials and 3 one-group pre-post-test; with 659 participants) were considered. The studies revealed a primary emphasis on gait speed measures within clinical tests, and a neglect of spatiotemporal gait variables. Most of the studies showed that CKD progression is associated with slowing of walking speed. No studies analysed the relation between gait parameters and fall risk.

CONCLUSIONS

There was a paucity of studies investigating aspects of gait quality in patients with CKD. In the majority of studies, only gait speed is analysed as a performance indicator. The relation between gait parameters and fall risk in CKD is not investigated. We formulate several recommendations to fill the current research gap, encourage the use of standardized gait analysis protocols that include assessment of spatiotemporal parameters in clinical care of patients with CKD, aimed at prevention of mobility decline and falls risk.

Wearable Technology and Physical Activity Behavior Change in Adults With Chronic Cardiometabolic Disease: A Systematic Review and Meta-Analysis

OBJECTIVE

To evaluate the effectiveness of wearable device interventions (eg, Fitbit) to improve physical activity (PA) outcomes (eg, steps/day, moderate to vigorous physical activity [MVPA]) in populations diagnosed with cardiometabolic chronic disease.

DATA SOURCE

Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses, an electronic search of 5 databases (Medline, PsychINFO, Scopus, Web of Science, and PubMed) was conducted.

STUDY INCLUSION AND EXCLUSION CRITERIA

Randomized controlled trials (RCTs) published between January 2000 and May 2018 that used a wearable device for the full intervention in adults (18+) diagnosed with a cardiometabolic chronic disease were included. Excluded trials included studies that used devices at pre-post only, devices that administered medication, and interventions with no prospective control group comparison.

DATA EXTRACTION

Thirty-five studies examining 4528 participants met the inclusion criteria. Study quality and RCT risk of bias were assessed using the Cochrane Collaboration Tool.

DATA SYNTHESIS

Meta-analyses to compute PA (eg, steps/day) and selected physical dispersion and summary effects were conducted using the raw unstandardized pooled mean difference (MD). Sensitivity analyses were examined.

RESULTS

Statistically significant increases in PA steps/day (MD = 2592 steps/day; 95% confidence interval [CI]: 1689-3496) and MVPA min/wk (MD = 36.31 min/wk; 95% CI: 18.33-54.29) were found for the intervention condition.

CONCLUSION

Wearable devices positively impact physical health in clinical populations with cardiometabolic diseases. Future research using the most current technologies (eg, Fitbit) will serve to amplify these findings.

Inertial sensors versus standard systems in gait analysis: a systematic review and meta-analysis

INTRODUCTION

The increasing popularity of inertial sensors in clinical practice is not supported by precise information on their reliability or guidelines for their use in rehabilitation. The authors investigated the state of the literature concerning the use of inertial sensors for gait analysis in both healthy and pathological adults comparing traditional systems. Furthermore, trying to define directions for clinicians.

EVIDENCE ACQUISITION

In accordance with the PRISMA statement, authors searched in PubMed, Web of Science and Scopus all paper published from January 1st, 2005 until December 31st, 2017. They included both healthy and pathological adults' subjects as population, wearable or inertial sensors used for gait analysis and compared with classical gait analysis performed in a Motion Lab as intervention and comparison, gait parameters as outcomes. Considering the methodological quality, authors focused on: sample; description of the study; type of gait analysis used for comparison; type of sensor; sensor placement on the body; gait task requested.

EVIDENCE SYNTHESIS

From a total of 888 articles, 16 manuscripts were selected and 7 of them were considered for meta-analysis for different gait parameters. Demographic data, tested devices, reference systems, test procedures and outcomes were analyzed.

CONCLUSIONS

Our results show a good agreement between inertial sensors and classical gait analysis for some gait parameters, supporting their use as a solution for capturing kinematic information over an extended space and time and even outside a laboratory in real-life conditions. Authors can support the use of portable inertial sensors for a practical gait analysis in clinical setting with good reliability. It will then be the experience of the clinician to direct the decision-making process.

Accelerometric Trunk Sensors to Detect Changes of Body Positions in Immobile Patients

Mobilization, verticalization and position change are mandatory for severely affected neurological patients in early neurorehabilitation in order to improve neurological status and prevent complications. However, with the exception of hospitals and rehabilitation facilities, this activity is not usually monitored and so far the automated monitoring of position changes in immobile patients has not been investigated. Therefore, we investigated whether accelerometers on the upper trunk could reliably detect body position changes in immobile patients. Thirty immobile patients in early neurorehabilitation (Barthel Index ≤ 30) were enrolled. Two tri-axial accelerometers were placed on the upper trunk and on the thigh. Information on the position and position changes of the subject were derived from accelerometer data and compared to standard written documentation in the hospital over 24 h. Frequency and duration of different body positions (supine, sidelying, sitting) were measured. Data are presented as mean ± SEM. Groups were compared using one-way ANOVA or Kruskal-Wallis-test. Differences were considered significant if p < 0.05. Trunk sensors detected 100% and thigh sensors 66% of position changes (p = 0.0004) compared to standard care documentation. Furthermore, trunk recording also detected additional spontaneous body position changes that were not documented in standard care (81.8 ± 4.4% of all position changes were documented in standard care documentation) (p < 0.0001). We found that accelerometric trunk sensors are suitable for recording position changes and mobilization of severely affected patients. Our findings suggest that using accelerometers for care documentation is useful for monitoring position changes and mobilization frequencies in and outside of hospital for severely affected neurological patients. Accelerometric sensors may be valuable in monitoring continuation of care plans after intensive neurorehabilitation.

The impact of wearable motion sensing technology on physical activity in older adults

BACKGROUND AND PURPOSE

Physical activity provides substantial health benefits. Older adults are less physically active than the rest of the population, and interventions that promote physical activity are needed. In this meta-analysis, we investigate how different wearable activity trackers (pedometers and accelerometers) may impact physical activity levels in older adults.

METHODS

We searched MEDLINE, Embase and CINAHL for randomized controlled trials including participants that were ≥65 years, using wearable activity trackers with the intent of increasing physical activity. Studies whose comparator groups were engaged in active or inactive interventions, such as continued a physical therapy program or goal-setting counseling, were not excluded simply for implementing co-interventions. We used random-effects models to produce standardized mean differences (SMDs) for physical activity outcomes. Heterogeneity was measured using I².

RESULTS

Nine studies met the eligibility criteria: Four using accelerometers, four using pedometers, and one comparing accelerometers and pedometers, for a total number of 939 participants. Using pooled data, we found a statistically significant effect of using accelerometers (SMD = 0.43 (95%CI 0.19-0.68), I² = 1.6%, p = 0.298), but not by using pedometers (SMD = 0.17 (95%CI -0.08-0.43), I² = 37.7%, p = 0.174) for increasing physical activity levels.

DISCUSSION AND CONCLUSIONS

In this study, we found that accelerometers, alone or in combination with other co-interventions, increased physical activity in older adults however pedometers were not found to increase physical activity. The high risk of bias found in most studies limits these findings. High quality studies that isolate the effects of accelerometers on physical activity changes are needed.

A smartphone-based solution to monitor daily physical activity in a care home

INTRODUCTION

In an ageing population, increasing chronic disease prevalence puts a high economic burden on society. Physical activity plays an important role in disease prevention and should therefore be promoted in the elderly.

METHODS

In this study, a mobile health (mHealth) system was implemented in a care home setting to monitor and promote elderly peoples' daily activity. The physical activity of 20 elderly people (8 female and 12 male, aged 81 ± 9 years old) was monitored over 10 weeks using the mHealth system, consisting of a smartphone and heart rate belt. Feedback on physical activity was provided weekly. A reference performance test battery derived from the Senior Fitness Test determined the participants' physical fitness.

RESULTS

Activity levels increased from week 1 onwards, peaking at week 5, and decreasing slightly until week 10. This illustrates that the use of mHealth and feedback on physical activity can motivate the elderly to become more active, but that the effect is transient without other incentives. Bio-data from the mHealth system were translated into a fitness score explaining 65% of the test battery's variance. After separating the elderly into three groups depending on physical fitness determined from the test battery, classification based on the fitness score resulted in a correct classification rate of 67.3%.

DISCUSSION

This study demonstrates that an mHealth system can be implemented in a care home setting to motivate activity of the elderly, and that the bio-data can be translated in a fitness score predicting the outcome of labour-intensive tests.

Preliminary concurrent validity of the Fitbit-Zip and ActiGraph activity monitors for measuring steps in people with polymyalgia rheumatica

BACKGROUND

Activity monitors provide objective measurements of physical activity, however, the accuracy of these devices in people with polymyalgia rheumatica (PMR) is unknown. Therefore, this study aimed to obtain preliminary evidence of the accuracy of two activity monitors and explore if clinical and gait-related factors altered device accuracy in people with PMR.

METHODS

The ActiGraph with low frequency extension (+LFE) and standard (-LFE) algorithms, Fitbit-Zip (waist) and Fitbit-Zip (shirt) were concurrently tested using a two-minute walk test (2MWT) and stairs test in 27 people with PMR currently treated with prednisolone. To determine accuracy, activity monitor step-count was compared to a gold-standard step-count (GSSC; calculated from video recording) using Bland-Altman plots.

RESULTS

The Fitbit-Zip (waist) achieved closest agreement to the GSSC for the 2MWT (mean bias (95%CI): 10 (-3, 23); 95%LOA: -55, 74). The ActiGraph (+LFE) achieved closest agreement to the GSSC for the stairs test (mean bias (95%CI): 0 (-1, 1); 95%LOA: -5, 5). The ActiGraph (-LFE) performed poorly in both tests. All devices demonstrated reduced accuracy in participants with lower gait velocity, reduced stride length, longer double-limb support phase and greater self-reported functional impairment.

CONCLUSION

Our preliminary results suggest that in controlled conditions, the Fitbit-Zip fairly accurately measures step-count during walking in people with PMR receiving treatment. However, device error was greater than data published in healthy people. The ActiGraph may not be recommended without activation of the LFE. We identified clinical and gait-related factors associated with higher levels of functional impairment that reduced device accuracy. Further work is required to evaluate the validity of the activity monitors in field conditions.

Reliability and validity of the inertial sensor-based Timed "Up and Go" test in individuals affected by stroke

The instrumented Timed "Up and Go" test (iTUG) has the potential for playing an important role in providing clinically useful information regarding an individual's balance and mobility that cannot be derived from the original single-outcome Timed "Up and Go" test protocol. The purpose of this study was to determine the reliability and validity of the iTUG using body-fixed inertial sensors in people affected by stroke. For test-retest reliability analysis, 14 individuals with stroke and 25 nondisabled elderly patients were assessed. For validity analysis, an age-matched comparison of 12 patients with stroke and 12 nondisabled controls was performed. Out of the 14 computed iTUG metrics, the majority showed excellent test-retest reliability expressed by high intraclass correlation coefficients (range 0.431-0.994) together with low standard error of measurement and smallest detectable difference values. Bland-Altman plots demonstrated good agreement between two repeated measurements. Significant differences between patients with stroke and nondisabled controls were found in 9 of 14 iTUG parameters analyzed. Consequently, these results warrant the future application of the inertial sensor-based iTUG test for the assessment of physical deficits poststroke in longitudinal study designs.

Measuring Activity Performance of Older Adults Using the activPAL: A Rapid Review

Current measures of physical activity and sedentary behaviors such as questionnaires and functional assessments are insufficient to provide comprehensive data on older adults. In response, the use of activity monitors has increased. The purpose of this review was to summarize and assess the quality of observational literature on activity measuring of older adults using the activPAL activity monitor. Seventeen databases and a bibliography, compiled by the activPAL creators, were searched. Articles were included if they were in English, were peer-reviewed, included people 65 years or older, measured activity using the activPAL and reported at least one of the following outcomes: step count, hours upright, hours sitting/lying, hours stepping, or hours standing. The search revealed 404 titles; after exclusions 24 were included in the final review. Of these studies, one examined older adults from residential aged care, six from hospital in-patient clinics, nine from outpatient clinics and eight examined community-dwellers. Mean age ranged from 66.0 to 84.2 years. Not all studies reported similar outcome variables, preventing data pooling. The review found a lack of high quality articles. There may be limitations to using the activPAL among older adults but further research is required to examine its use in this population.

Classification of Daily Activities for the Elderly Using Wearable Sensors

Monitoring of activities of daily living (ADL) using wearable sensors can provide an objective indication of the activity levels or restrictions experienced by patients or elderly. The current study presented a two-sensor ADL classification method designed and tested specifically with elderly subjects. Ten healthy elderly were involved in a laboratory testing with 6 types of daily activities. Two inertial measurement units were attached to the thigh and the trunk of each subject. The results indicated an overall rate of misdetection being 2.8%. The findings of the current study can be used as the first step towards a more comprehensive activity monitoring technology specifically designed for the aging population.

Validity, reliability and feasibility of commercially available activity trackers in physical therapy for people with a chronic disease: a study protocol of a mixed methods research

BACKGROUND

For older people and people with a chronic disease, physical activity provides health benefits. Patients and healthcare professionals can use commercially available activity trackers to objectively monitor (alterations in) activity levels and patterns and to support physical activity. However, insight in the validity, reliability, and feasibility of these trackers in people with a chronic disease is needed. In this article, a study protocol is described in which the validity, reliability (part A), and feasibility from a patient and therapist's point of view (part B) of commercially available activity trackers in daily life and health care is investigated.

METHODS

In part A, a quantitative cross-sectional study, an activity protocol that simulates everyday life activities will be used to determine the validity and reliability of nine commercially available activity trackers. Video recordings will act as the gold standard. In part B, a qualitative participatory action research study will be performed to gain insight in the use of activity trackers in peoples' daily life and therapy settings. Objective feasibility of the activity trackers will be measured with questionnaires, and subjective feasibility (experiences) will be explored in a community of practice. Physical therapists (n = 8) will regularly meet during 6 months to learn from each other regarding the actual use of activity trackers in therapy. Therapists and patients (n = 48) will decide together which tracker will be used in therapy and for which purpose (e.g., monitoring, goal setting). Data from the therapist' and patients' experiences will be collected by interviews (individual and focus groups) and analyzed by a directed content analysis. At the time of submission, selection of activity trackers, development of the activity protocol, and the ethical approval process are finished. Data collection and data processing are ongoing.

DISCUSSION

The relevance of the study as well as the advantages and disadvantages of several aspects of the chosen design are discussed. The results acquired from both study parts can be used to create decision aids that may assist therapists and people with a chronic disease in choosing a suitable activity tracker, and to facilitate use of these activity trackers in health care settings.

TRIAL REGISTRATION

Ethical approval has been obtained from two medical-ethical committees (nr. 15-N-109, 15-N-48 and MEC-15-07).

Levels of activity identification & sleep duration detection with a wrist-worn accelerometer-based device

In this study, a model for identifying the levels of physical activity (PA) with a wrist-worn accelerometer-based device has been proposed. The levels of identified PA have been categorized into rest/sleep, sedentary, light, moderate, and vigorous activity states by analyzing the data collected from 10 normal subjects. An activity-based sleep duration detection algorithm has been proposed and implemented thereafter to further distinguish activities between short period of rest and sleep. The model and method proposed in this study could be further used to monitor subject's daily PA status and sleep quality assessment in the future for various home-based healthcare applications.

Digitally enhanced recovery: Investigating the use of digital self-tracking for monitoring leisure time physical activity of cardiovascular disease (CVD) patients undergoing cardiac rehabilitation

Research has shown that physical activity is essential in the prevention and treatment of chronic diseases like cardiovascular disease (CVD). Smart wearables (e.g., smartwatches) are increasingly used to foster and monitor human behaviour, including physical activity. However, despite this increased usage, little evidence is available on the effects of smart wearables in behaviour change. The little research which is available typically focuses on the behaviour of healthy individuals rather than patients. In this study, we investigate the effects of using smart wearables by patients undergoing cardiac rehabilitation. A field experiment involving 29 patients was designed and participants were either assigned to the study group (N = 13 patients who finished the study and used a self-tracking device) or the control group (N = 16 patients who finished the study and did not use a device). For both groups data about physiological performance during cardiac stress test was collected at the beginning (baseline), in the middle (in week 6, at the end of the rehabilitation in the organized rehabilitation setting), and at the end of the study (after 12 weeks, at the end of the rehabilitation, including the organized rehabilitation plus another 6 weeks of self-organized rehabilitation). Comparing the physiological performance of both groups, the data showed significant differences. The participants in the study group not only maintained the same performance level as during the midterm examination in week 6, they improved performance even further during the six weeks that followed. The results presented in this paper provide evidence for positive effects of digital self-tracking by patients undergoing cardiac rehabilitation on performance of the cardiovascular system. In this way, our study provides novel insight about the effects of the use of smart wearables by CVD patients. Our findings have implications for the design of self-management approaches in a patient rehabilitation setting. In essence, the use of smart wearables can prolong the success of the rehabilitation outside of the organized rehabilitation setting.

Systematic review of the effectiveness of health-related behavioral interventions using portable activity sensing devices (PASDs)

BACKGROUND

Portable activity sensing devices (PASDs) have received significant interest as tools for objectively measuring activity-related parameters and promoting health-related outcomes. Studies of PASDs suggest the potential value of integrating them with behavioral interventions to improve intermediate and downstream clinical outcomes.

OBJECTIVES

This systematic review describes and evaluates evidence from controlled studies of interventions using PASDs on their effectiveness in health-related outcomes. Study quality was also assessed.

METHODS

A systematic literature search was performed of MEDLINE, Cochrane Central Register of Controlled Trials, PsycINFO, EMBASE, and CINAHL databases. We included English-language papers of controlled trials through 2015 reporting the effectiveness of PASDs in improving health-related outcomes in any population. We extracted and analyzed data on study characteristics including design, target population, interventions, and findings.

RESULTS

Seventeen trials met the inclusion criteria from a total of 9553 unique records. Study objectives varied greatly, but most sought to increase physical activity. Studies with a "passive" intervention arm using a PASD with minimal behavioral support generally did not demonstrate effectiveness in improving health-related outcomes. Interventions integrating PASDs with multiple behavioral change techniques were more likely to be effective, particularly for intermediate outcomes such as physical activity and weight loss. Trials had small sample sizes but were generally free of bias, except for blinding and selection bias.

CONCLUSION

There is insufficient evidence to draw a conclusion about the general health-related benefits of PASD interventions. PASD interventions may improve intermediate outcomes when coupled with multiple behavioral change techniques. Devices alone or with minimal behavioral change support are insufficient to change health-related outcomes.

Development and clinical application of a computer-aided real-time feedback system for detecting in-bed physical activities

BACKGROUND AND OBJECTIVE

Being bedridden long-term can cause deterioration in patients' physiological function and performance, limiting daily activities and increasing the incidence of falls and other accidental injuries. Little research has been carried out in designing effective detecting systems to monitor the posture and status of bedridden patients and to provide accurate real-time feedback on posture. The purposes of this research were to develop a computer-aided system for real-time detection of physical activities in bed and to validate the system's validity and test-retest reliability in determining eight postures: motion leftward/rightward, turning over leftward/rightward, getting up leftward/rightward, and getting off the bed leftward/rightward.

METHODS

The in-bed physical activity detecting system consists mainly of a clinical sickbed, signal amplifier, a data acquisition (DAQ) system, and operating software for computing and determining postural changes associated with four load cell sensing components. Thirty healthy subjects (15 males and 15 females, mean age = 27.8 ± 5.3 years) participated in the study. All subjects were asked to execute eight in-bed activities in a random order and to participate in an evaluation of the test-retest reliability of the results 14 days later. Spearman's rank correlation coefficient was used to compare the system's determinations of postural states with researchers' recordings of postural changes. The test-retest reliability of the system's ability to determine postures was analyzed using the interclass correlation coefficient ICC(3,1).

RESULTS

The system was found to exhibit high validity and accuracy (r = 0.928, p < 0.001; accuracy rate: 87.9%) in determining in-bed displacement, turning over, sitting up, and getting off the bed. The system was particularly accurate in detecting motion rightward (90%), turning over leftward (83%), sitting up leftward or rightward (87-93%), and getting off the bed (100%). The test-retest reliability ICC(3,1) value was 0.968 (p < 0.001).

CONCLUSIONS

The system developed in this study exhibits satisfactory validity and reliability in detecting changes in-bed body postures and can be beneficial in assisting caregivers and clinical nursing staff in detecting the in-bed physical activities of bedridden patients and in developing fall prevention warning systems.