Postural Transitions during Activities of Daily Living Could Identify Frailty Status: Application of Wearable Technology to Identify Frailty during Unsupervised Condition

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.

Scale development to evaluate differences between concern about falling and fear of falling: the concern and fear of falling evaluation

Purpose

Individuals with multiple sclerosis (MS) experience fear of falling (FOF), which is associated with negative health and quality-of-life consequences. Prior research has used FOF and concern about falling (CAF) interchangeably, but persons with MS report that CAF and FOF represent separate constructs that lie on a continuum. Unfortunately, no scale exists to understand the differences between CAF and FOF. Therefore, we developed a novel questionnaire, the Concern and Fear of Falling Evaluation (CAFFE), in which respondents rank their CAF and FOF on a continuum across various activities. This study aims to describe the scale development process and examine its psychometric properties.

Methods

In a single online survey, MS participants responded to demographic questionnaires, indicated whether they experience CAF and FOF, and completed the CAFFE. Psychometric evaluation of the CAFFE involved internal consistency, split-half cross validation, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA).

Results

Out of 1,025 respondents, 64.6% reported CAF and 47.2% reported FOF. The EFA yielded a two-factor solution encompassing activities in open (factor 1) and closed environments (factor 2). The CFA replicated this two-factor solution and the CAFFE demonstrated excellent internal consistency (α = 0.98).

Conclusion

The 27-item CAFFE is a highly reliable and valid measure capturing the tipping point at which point CAF moves to FOF. Future research should seek to define the tipping point from the MS community, as CAF may be an adaptive mechanism, whereas FOF may be a maladaptive behavior.

Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review

BACKGROUND

Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is mostly focused on biological variables; however, it is likely that this diagnosis could fail owing to the high biological variability in this syndrome. Therefore, artificial intelligence (AI) could be a potential strategy to identify and diagnose this complex and multifactorial geriatric syndrome.

OBJECTIVE

The objective of this scoping review was to analyze the existing scientific evidence on the use of AI for the identification and diagnosis of FS in older adults, as well as to identify which model provides enhanced accuracy, sensitivity, specificity, and area under the curve (AUC).

METHODS

A search was conducted using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines on various databases: PubMed, Web of Science, Scopus, and Google Scholar. The search strategy followed Population/Problem, Intervention, Comparison, and Outcome (PICO) criteria with the population being older adults; intervention being AI; comparison being compared or not to other diagnostic methods; and outcome being FS with reported sensitivity, specificity, accuracy, or AUC values. The results were synthesized through information extraction and are presented in tables.

RESULTS

We identified 26 studies that met the inclusion criteria, 6 of which had a data set over 2000 and 3 with data sets below 100. Machine learning was the most widely used type of AI, employed in 18 studies. Moreover, of the 26 included studies, 9 used clinical data, with clinical histories being the most frequently used data type in this category. The remaining 17 studies used nonclinical data, most frequently involving activity monitoring using an inertial sensor in clinical and nonclinical contexts. Regarding the performance of each AI model, 10 studies achieved a value of precision, sensitivity, specificity, or AUC ≥90.

CONCLUSIONS

The findings of this scoping review clarify the overall status of recent studies using AI to identify and diagnose FS. Moreover, the findings show that the combined use of AI using clinical data along with nonclinical information such as the kinematics of inertial sensors that monitor activities in a nonclinical context could be an appropriate tool for the identification and diagnosis of FS. Nevertheless, some possible limitations of the evidence included in the review could be small sample sizes, heterogeneity of study designs, and lack of standardization in the AI models and diagnostic criteria used across studies. Future research is needed to validate AI systems with diverse data sources for diagnosing FS. AI should be used as a decision support tool for identifying FS, with data quality and privacy addressed, and the tool should be regularly monitored for performance after being integrated in clinical practice.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.

Technologies for frailty, comorbidity, and multimorbidity in older adults: a systematic review of research designs

BACKGROUND

Frailty, neurodegeneration and geriatric syndromes cause a significant impact at the clinical, social, and economic level, mainly in the context of the aging world. Recently, Information and Communication Technologies (ICTs), virtual reality tools, and machine learning models have been increasingly applied to the care of older patients to improve diagnosis, prognosis, and interventions. However, so far, the methodological limitations of studies in this field have prevented to generalize data to real-word. This review systematically overviews the research designs used by studies applying technologies for the assessment and treatment of aging-related syndromes in older people.

METHODS

Following the PRISMA guidelines, records from PubMed, EMBASE, and Web of Science were systematically screened to select original articles in which interventional or observational designs were used to study technologies' applications in samples of frail, comorbid, or multimorbid patients.

RESULTS

Thirty-four articles met the inclusion criteria. Most of the studies used diagnostic accuracy designs to test assessment procedures or retrospective cohort designs to build predictive models. A minority were randomized or non-randomized interventional studies. Quality evaluation revealed a high risk of bias for observational studies, while a low risk of bias for interventional studies.

CONCLUSIONS

The majority of the reviewed articles use an observational design mainly to study diagnostic procedures and suffer from a high risk of bias. The scarce presence of methodologically robust interventional studies may suggest that the field is in its infancy. Methodological considerations will be presented on how to standardize procedures and research quality in this field.

Sensor-Based Assessment of Variability in Daily Physical Activity and Frailty

INTRODUCTION

Frailty is a common geriatric syndrome associated with decline in physiological reserve. While several digital biomarkers of daily physical activity (DPA) have been used in frailty assessment, the association between DPA variability and frailty is still not clear. The goal of this study was to determine the association between frailty and DPA variability.

METHODS

This is an observational cross-sectional study conducted between September 2012 and November 2013. Older adults (≥65 years), without any severe mobility disorder, and the ability to walk 10 m (with or without an assistive device) were eligible for the study. DPA including sitting, standing, walking, lying, and postural transition were recorded for 48 h continuously. DPA variability was analyzed from two perspectives: (i) DPA duration variability in terms of coefficient of variation (CoV) of sitting, standing, walking, and lying down durations; and (ii) DPA performance variability in terms of CoV of sit-to-stand (SiSt) and stand-to-sit (StSi) durations and stride time (i.e., slope of power spectral density - PSD).

RESULTS

Data was analyzed from 126 participants (44 non-frail, 60 pre-frail, and 22 frail). For DPA duration variability, CoV of lying and walking duration was significantly larger among non-frail compared to pre-frail and frail groups (p < 0.03, d = 0.89 ± 0.40). For DPA performance variability, StSi CoV and PSD slope were significantly smaller for non-frail compared to pre-frail and frail groups (p < 0.05, d = 0.78 ± 0.19).

CONCLUSION

Lower DPA duration variability in pre-frail and frail groups may be attributed to the set daily routines frail older adults tend to follow, compared to variable physical activity routines of non-frail older adults. Higher DPA performance variability in the frail group may be attributed to reduced physiological capabilities toward walking for longer durations and the reduced muscle strength in the lower extremities, leading to incosistency in performing postural transitions.

Benefits and Barriers of Technology for Home Function and Mobility Assessment: Perspectives of Older Patients With Blood Cancers, Caregivers, and Clinicians

PURPOSE

Advances in digital health technology can overcome barriers to measurement of function and mobility for older adults with blood cancers, but little is known about how older adults perceive such technology for use in their homes.

METHODS

To characterize potential benefits and barriers associated with using technology for home functional assessment, we conducted three semistructured focus groups (FGs) in January 2022. Eligible patients came from the Older Adult Hematologic Malignancies Program at Dana-Farber Cancer Institute (DFCI), which includes adults 73 years and older enrolled during their initial consult with their oncologist. Eligible caregivers were 18 years and older and identified by enrolled patients as their primary caregiver. Eligible clinicians were practicing DFCI hematologic oncologists, nurse practitioners, or physician assistants with ≥2 years of clinical experience. A qualitative researcher led thematic analysis of FG transcripts to identify key themes.

RESULTS

Twenty-three participants attended the three FGs: eight patients, seven caregivers, and eight oncology clinicians. All participants valued function and mobility assessments and felt that technology could overcome barriers to their measurement. We identified three themes related to potential benefits: making it easier for oncology teams to consider function and mobility; providing standardized, objective data; and facilitating longitudinal data. We also identified four themes related to barriers to home functional assessment: concerns related to privacy and confidentiality, burden of measuring additional patient data, challenges in operating new technology, and concerns related to data improving care.

CONCLUSION

These data suggest that specific concerns raised by older patients, caregivers, and oncology clinicians must be addressed to improve acceptability and uptake of technology used to measure function and mobility in the home.

The Reliability and Validity of the Lie-to-Sit-to-Stand-to-Walk Transfer (LSSWT) Test in Knee Osteoarthritis

Background

Several neuromuscular impairments may be observed in older patients with knee osteoarthritis (OA), increasing the risk of falling, which is common during transfer activities. The Lie-to-Sit-to- Stand-to-Walk Transfer (LSSWT) test was developed to evaluate complex transfer abilities. The study aims to investigate the reliability and validity of LSSWT in patients with knee OA.

Methods

Twenty-nine patients with knee OA were included in this study. The LSSWT, Timed up and go test (TUG), and Western Ontario and McMaster Universities Arthritis Index (WOMAC) were administered to the patients. Patients rested for at least an hour between the trials to avoid fatigue.

Results

The LSSWT has excellent reliability and high validity in patients with knee OA. The relative (ICC coefficient) and absolute (SEM and SRD95) reliability values are 0.96 (95% CI: 0.91-0.98), 1.00, and 2,75, respectively. The Pearson correlation coefficient of the LSSWT with the TUG is 0.73 (p < 0.01), and the Spearmen correlation coefficient of the LSSWT with the WOMAC is 0.54 (p < 0.05).

Conclusions

The LSSWT is highly reliable and valid in knee OA and is recommended for routine dynamic balance establishment. Having a low minimal clinically important difference shows the LSSWT's sensitivity. The LSSWT can easily identify dynamic balance deficits in knee OA patients and help prevent fall incidents.

Executive and Motor Functions in Older Individuals with Cognitive Impairment

Background: A current research trend is the examination of the interplay between cognitive functioning, higher-order processes, and motor efficiency in late adulthood. However, the association between motor and cognitive functions when cognitive decline occurs has not been extensively explored. This study investigated whether gait features, functional mobility, and handgrip strength were associated with executive functions in older people with mild cognitive impairment (MCI) or dementia. Methods: 127 older participants (M_age = 77.9 years, SD = 5.8 years) who had received a diagnosis of MCI and dementia voluntarily took part in the study. A battery of tests assessing global cognitive function, executive functions, muscular strength, functional mobility, and spatio-temporal parameters of gait was completed by the participants. Results: Statistically significant correlations were obtained between global cognitive function, executive functions, and motor efficiency measures. Moreover, a series of regression analyses showed that 8–13% of the variance of several motor parameters was predicted by several executive functions. Additionally, walking, functional mobility, and global cognitive function predicted 53–71% of the variance relative to the occurrence of dementia. In conclusion, motor functioning is closely related to cognitive functioning in late adulthood. Conclusions: The assessment of muscular strength and functional mobility should be promoted in clinical settings.

Randomized Phase 2 Study of ACE-083 in Patients With Charcot-Marie-Tooth Disease

BACKGROUND AND OBJECTIVES

The goal of this work was to determine whether locally acting ACE-083 is safe and well tolerated and increases muscle volume, motor function, and quality of life (QoL) in adults with Charcot-Marie-Tooth disease (CMT) type 1.

METHODS

This phase 2 study enrolled adults with CMT1 or CMTX (N = 63). Part 1 was open label and evaluated the safety and tolerability of different dose levels of ACE-083 for use in part 2. Part 2 was a randomized, placebo-controlled, 6-month study of 240 mg/muscle ACE-083 injected bilaterally into the tibialis anterior muscle, followed by a 6-month, open-label extension in which all patients received ACE-083. Pharmacodynamic endpoints included total muscle volume (TMV; primary endpoint), contractile muscle volume (CMV), and fat fraction. Additional secondary endpoints included 6-minute walk test, 10-m walk/run, muscle strength, and QoL. Safety was assessed with treatment-emergent adverse events (TEAEs) and clinical laboratory tests.

RESULTS

In part 1 (n = 18), ACE-083 was generally safe and well tolerated at all dose levels, with no serious adverse events, TEAEs of grade 3 or greater, or death reported. In part 2 (n = 45 enrolled, n = 44 treated), there was significantly greater change in TMV with ACE-083 compared with placebo (least-squares mean difference 13.5%; p = 0.0096). There was significant difference between ACE-083 and placebo for CMV and change in ankle dorsiflexion strength. Fat fraction and all other functional outcomes were not significantly improved by ACE-083. Moderate to mild injection-site reactions were the most common TEAEs.

DISCUSSION

Despite significantly increased TMV and CMV, patients with CMT receiving ACE-083 in tibialis anterior muscles did not demonstrate greater functional improvement compared with those receiving placebo.

TRIAL REGISTRATION INFORMATION

Clinical Trials Registration: NCT03124459.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that intramuscular ACE-083 is safe and well tolerated and increases total muscle volume after 6 months of treatment in adults with CMT1 or CMTX.

Association between free-living sit-to-stand transition characteristics, and lower-extremity performance, fear of falling, and stair negotiation difficulties among community-dwelling 75 to 85-year-old adults

Background

Good sit-to-stand (STS) performance is an important factor in maintaining functional independence. This study investigated whether free-living STS transition volume and intensity, assessed by a thigh-worn accelerometer, is associated with characteristics related to functional independence.

Methods

Free-living thigh-worn accelerometry was recorded continuously for 3–7 days in a population-based sample of 75-, 80-, and 85-year-old community-dwelling people (479 participants; women n = 287, men n = 192). The records were used to evaluate the number and intensity (angular velocity of the STS phase) of STS transitions. Associations with short physical performance battery (SPPB), 5-times-sit-to-stand test (5×STS), isometric knee extension force, self-reported fear of falls, and self-reported difficulty in negotiating stairs were also assessed.

Results

The number of STS transitions, mean and maximal angular velocity were lower in older age groups (p < .05). All variables were higher in men than in women (p < .001) and were positively associated with SPPB total points, knee extension force (r ranged from 0.18 to 0.39, all p < .001) and negatively associated with 5×STS (r = −0.13 – −0.24, all p < .05), lower extremity functional limitations (p < .01), fear of falls (p < .01), and stair negotiation difficulties (p < .01).

Conclusions

Free-living STS characteristics were related to lower-extremity performance, lower extremity functional limitations, self-reported fear of falls, and stair negotiation difficulties, which can be a sensitive indicator of impending functional decline. Moreover, STS transitions may provide an indicator of adequacy of lower-limb muscle strength among older individuals.

Assessment of Thigh Angular Velocity by an Activity Monitor to Describe Sit-to-Stand Performance

The assessment of sit-to-stand (STS) performance is highly relevant, especially in older persons, but testing STS performance in the laboratory does not necessarily reflect STS performance in daily life. Therefore, the aim was to validate a wearable sensor-based measure to be used under unsupervised daily life conditions. Since thigh orientation from horizontal to vertical is characteristic for STS movement, peak angular velocity (PAV) of the thigh was chosen as the outcome variable. A total of 20 younger and older healthy persons and geriatric patients (mean age: 55.5 ± 20.8 years; 55% women) with a wide range of STS performance were instructed to stand up from a chair at their usual pace. STS performance was measured by an activity monitor, force plates, and an opto-electronic system. The association between PAV measured by the thigh-worn activity monitor and PAV measured by the opto-electronic system (gold standard) was r = 0.74. The association between PAV measured by the thigh-worn activity monitor and peak power measured by force plate and opto-electronic system was r = 0.76. The Intra-Class Coefficient (ICC) of agreement between the 2 trials was ICC_(A,1) = 0.76. In this sample of persons with a wide range of physical performance, PAV as measured by a thigh-worn acceleration sensor was a valid and reliable measure of STS performance.

Wearable inertial sensors for human movement analysis: a five-year update

INTRODUCTION

The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings.

AREAS COVERED

Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings.

EXPERT OPINION

IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

Associations of objectively measured physical activity and sedentary behaviour with fall-related outcomes in older adults: a systematic review

BACKGROUND

Higher physical activity (PA) and lower sedentary behaviour (SB) are associated with better muscle strength, balance, and functional ability, which are imperative for avoiding falls. This systematic review aimed to describe the association between objectively measured PA and SB with falls, fear of falling, and fractures.

METHODS

Six databases were searched from inception to July 21, 2020 for articles reporting the association of objectively measured PA/SB with falls, fear of falling, and/or fractures in community-dwelling older adults ≥60 years old. Results were synthesized in effect-direction heat maps and albatross plots expressed as Pearson's correlation coefficients (R).

RESULTS

A total of 43 articles were included, representing 27,629 (range 26 to 5,545) community-dwelling older adults (mean [SD] age 76.6 [8.4] years, 47% female). Longitudinal associations were reported in 13 articles and cross-sectional associations in 30. Falls were reported in 11 articles, fear of falling in 18 and fractures in 2. Higher PA and lower SB were associated with less fear of falling (median [interquartile range] Rs = steps: -0.214 [0.249; -0.148], total PA: -0.240 [0.267; -0.144], and moderate-to-vigorous PA: -0.180 [0.382; -0.121]), but these associations did not extend to falls or fractures, which showed inconsistent effect directions.

CONCLUSION

Fear of falling is associated with less engagement in PA and more SB, thus indicating that it is a psychological barrier to an active lifestyle. Varying effect directions for associations between PA and SB with falls and fractures may provide evidence for non-linear associations and require further research considering details of the fall or fracture incident.

PROSPERO REGISTRATION NUMBER

CRD42018103910.

Digital Biomarkers of Physical Frailty and Frailty Phenotypes Using Sensor-Based Physical Activity and Machine Learning

Remote monitoring of physical frailty is important to personalize care for slowing down the frailty process and/or for the healthy recovery of older adults following acute or chronic stressors. Taking the Fried frailty criteria as a reference to determine physical frailty and frailty phenotypes (slowness, weakness, exhaustion, inactivity), this study aimed to explore the benefit of machine learning to determine the least number of digital biomarkers of physical frailty measurable from a pendant sensor during activities of daily living. Two hundred and fifty-nine older adults were classified into robust or pre-frail/frail groups based on the physical frailty assessments by the Fried frailty criteria. All participants wore a pendant sensor at the sternum level for 48 h. Of seventeen sensor-derived features extracted from a pendant sensor, fourteen significant features were used for machine learning based on logistic regression modeling and a recursive feature elimination technique incorporating bootstrapping. The combination of percentage time standing, percentage time walking, walking cadence, and longest walking bout were identified as optimal digital biomarkers of physical frailty and frailty phenotypes. These findings suggest that a combination of sensor-measured exhaustion, inactivity, and speed have potential to screen and monitor people for physical frailty and frailty phenotypes.

Frailty assessment and interventions for community-dwelling older adults: a rapid review

Frailty is a syndrome involving increased vulnerability that usually develops from age-related decline in physiological reserves and function in multiple organ systems, resulting in an impaired ability to respond to acute changes in health conditions. It is imperative that healthcare providers who work with older adults in primary care and community settings understand how to assess frailty and can identify appropriate interventions. This article reports the results of a rapid review that examined how frailty is assessed in community-dwelling older adults and what interventions are used to address frailty in this population.

How wearable sensors have been utilised to evaluate frailty in older adults: a systematic review

BACKGROUND

Globally the population of older adults is increasing. It is estimated that by 2050 the number of adults over the age of 60 will represent over 21% of the world's population. Frailty is a clinical condition associated with ageing resulting in an increase in adverse outcomes. It is considered the greatest challenge facing an ageing population affecting an estimated 16% of community-dwelling populations worldwide.

AIM

The aim of this systematic review is to explore how wearable sensors have been used to assess frailty in older adults.

METHOD

Electronic databases Medline, Science Direct, Scopus, and CINAHL were systematically searched March 2020 and November 2020. A search constraint of articles published in English, between January 2010 and November 2020 was applied. Papers included were primary observational studies involving; older adults aged > 60 years, used a wearable sensor to provide quantitative measurements of physical activity (PA) or mobility and a measure of frailty. Studies were excluded if they used non-wearable sensors for outcome measurement or outlined an algorithm or application development exclusively. The methodological quality of the selected studies was assessed using the Appraisal Tool for Cross-sectional Studies (AXIS).

RESULTS

Twenty-nine studies examining the use of wearable sensors to assess and discriminate between stages of frailty in older adults were included. Thirteen different body-worn sensors were used in eight different body-locations. Participants were community-dwelling older adults. Studies were performed in home, laboratory or hospital settings. Postural transitions, number of steps, percentage of time in PA and intensity of PA together were the most frequently measured parameters followed closely by gait speed. All but one study demonstrated an association between PA and level of frailty. All reports of gait speed indicate correlation with frailty.

CONCLUSIONS

Wearable sensors have been successfully used to evaluate frailty in older adults. Further research is needed to identify a feasible, user-friendly device and body-location that can be used to identify signs of pre-frailty in community-dwelling older adults. This would facilitate early identification and targeted intervention to reduce the burden of frailty in an ageing population.

Frailty Level Classification of the Community Elderly Using Microsoft Kinect-Based Skeleton Pose: A Machine Learning Approach

Frailty is one of the most important geriatric syndromes, which can be associated with increased risk for incident disability and hospitalization. Developing a real-time classification model of elderly frailty level could be beneficial for designing a clinical predictive assessment tool. Hence, the objective of this study was to predict the elderly frailty level utilizing the machine learning approach on skeleton data acquired from a Kinect sensor. Seven hundred and eighty-seven community elderly were recruited in this study. The Kinect data were acquired from the elderly performing different functional assessment exercises including: (1) 30-s arm curl; (2) 30-s chair sit-to-stand; (3) 2-min step; and (4) gait analysis tests. The proposed methodology was successfully validated by gender classification with accuracies up to 84 percent. Regarding frailty level evaluation and prediction, the results indicated that support vector classifier (SVC) and multi-layer perceptron (MLP) are the most successful estimators in prediction of the Fried’s frailty level with median accuracies up to 97.5 percent. The high level of accuracy achieved with the proposed methodology indicates that ML modeling can identify the risk of frailty in elderly individuals based on evaluating the real-time skeletal movements using the Kinect sensor.

Self-efficacy training as an adjunct to exercise in a person with progressive multiple sclerosis: a case report

Background: Increasing self-efficacy to exercise and minimizing disease-related barriers has been shown to improve physical activity levels and quality of life (QOL) in persons with multiple sclerosis (MS). Currently, little research has examined exercise self-efficacy in persons with more advanced MS. Purpose: Explore the effects of a self-efficacy plus exercise intervention on physical activity endurance and level, QOL, and fatigue in an individual with advanced MS and low self-efficacy.Methods: The participant was a 60-year-old, severely disabled female with secondary progressive MS and an Expanded Disability Status Score (EDSS) of 8. The 8-week intervention consisted of weekly discussions and MS-related education; four one-on-one sessions with a MS "mentor;" daily journal to record sleep quality, fatigue level, and physical activity. Outcomes included a modified 5-meter walk test (5MWT), MS Impact Scale (MSIS-29), Exercise Self-Efficacy Scale (EX-ES), Modified Fatigue Impact Scale (MFIS), MS Self-Efficacy Scale (MS-SES), Patient Health Questionnaire-9 (PHQ-9), and daily physical activity monitoring. Outcomes were assessed at baseline (week 0), post-intervention (week 8), and 8 weeks post intervention (week 16). The participant continued her regular exercise routine independently throughout the study period.Results: There were notable improvements in EX-ES, MFIS, PHQ-9, MSIS-29 psychological subscale, sleep quality, and morning fatigue ratings post intervention, some of which were retained at follow up.Conclusion: The findings illustrate that an 8-week self-efficacy intervention increased exercise self-efficacy, QOL, and reduced perceived fatigue in a severely disabled individual with progressive MS. Future research should examine self-efficacy interventions in a larger sample size of persons with progressive MS.

Information and Communication Technologies for Managing Frailty: A Systematic Literature Review

Frailty is a prevalent condition among Canadians; over one million are diagnosed as medically frail, and in the next ten years this number will double. Information and telecommunication technologies can provide a low-cost method for managing frailty more proactively. This study aims to examine the range and extent of information and telecommunication technologies for managing frailty in older adults, their technology readiness level, the evidence, and the associated outcomes. A systematic literature review was conducted. Four databases were searched for studies: Medline, EMBASE, CINAHL, and Web of Science. In total, we included 19 studies (out of 9,930) for the data abstraction. Overall, our findings indicate that (1) the proposed frailty phenotype is the most common ground truth to be used for assessing frailty; (2) the most common uses of information and telecommunication technologies for managing frailty are detection, and monitoring and detection, while interventional studies on frailty are very rare; (3) the five main types of information and telecommunication technologies for managing frailty in older adults are information and telecommunication technology-based platforms, smartphones, telemonitoring (home monitoring), wearable sensors and devices (commercial off-the-shelf), and multimedia formats for online access; (4) the technology readiness level of information and telecommunication technologies for managing frailty in older adults is the “Technology Demonstration” level, i.e., not yet ready to be operated in an actual operating environment; and (5) the level of evidence is still low for information and telecommunication technology studies that manage frailty in older adults. In conclusion, information and telecommunication technologies for managing frailty in the older adult population are not yet ready to be full-fledged technologies for this purpose.

Decrease in Mobility during the COVID-19 Pandemic and Its Association with Increase in Depression among Older Adults: A Longitudinal Remote Mobility Monitoring Using a Wearable Sensor

Background: Social isolation during COVID-19 may negatively impact older adults’ wellbeing. To assess its impact, we measured changes in physical activity and sleep among community-dwelling older adults, from pre-to post-pandemic declaration. Method: Physical activity and sleep in older adults (n = 10, age = 77.3 ± 1.9 years, female = 40%) were remotely assessed within 3-month pre-to 6-month post-pandemic declaration using a pendant-wearable system. Depression was assessed pre-and post-pandemic declaration using the Center for Epidemiologic Studies Depression scale and was compared with 48 h continuous physical activity monitoring data before and during pandemic. Results: Compared to pre-pandemic, post-pandemic time spent in standing declined by 32.7% (Cohen’s d = 0.78, p < 0.01), walking by 52.2% (d = 1.1, p < 0.01), step-counts by 55.1% (d = 1.0, p = 0.016), and postural transitions by 44.6% (d = 0.82, p = 0.017) with increase in sitting duration by 20.5% (d = 0.5, p = 0.049). Depression symptoms increased by 150% (d = 0.8, p = 0.046). Interestingly, increase in depression was significantly correlated with unbroken-prolong sitting bout (ρ = 0.677, p = 0.032), cadence (ρ = −0.70, p = 0.024), and sleep duration (ρ = −0.72, p = 0.019). Conclusion: This is one of the early longitudinal studies highlighting adverse effect of the pandemic on objectively assessed physical activity and sleep in older adults. Our observations showed need for timely intervention to mitigate hard to reverse consequences of decreased physical activity such as depression.

Objectively measured physical activity is associated with frailty in community-dwelling older adults: A systematic review

OBJECTIVE

The later-age shift towards physical inactivity and sedentary behaviour is associated with comorbidity and reduced function: markers of frailty. Whether these behaviours relate to frailty has yet to be thoroughly studied using objective measurements. This study aimed to summarise the associations of objectively measured habitual physical activity and sedentary behaviour with frailty in community-dwelling older adults.

STUDY DESIGN AND SETTING

Six databases were searched from inception to July 21st 2020. Articles analyzing objectively measured physical activity and/or sedentary behaviour with frailty in community-dwelling adults ≥60 years old were included. Synthesis of included articles was performed using effect direction heat maps and albatross plots.

RESULTS

The search identified 23 articles across 18 cohorts, including 7,696 total participants with a mean age of 69.3±8.1 years, and 56.9% female. All but one article were cross-sectional. Lower moderate-to-vigorous and total physical activity, steps, postural transitions, and energy expenditure were associated with frailty. The use of multifactorial or physical frailty definitions did not alter associations. Median effect sizes for the associations of all physical activity and sedentary behaviour measures with frailty were β = -0.272 [-0.381, -0.107] and β = 0.100 [0.001, 0.249], respectively.

CONCLUSION

Objective measures of physical activity are associated with frailty, regardless of frailty definition.

Unobtrusive Sensors for the Assessment of Older Adult's Frailty: A Scoping Review

Ubiquity (devices becoming part of the context) and transparency (devices not interfering with daily activities) are very significant in healthcare monitoring applications for elders. The present study undertakes a scoping review to map the literature on sensor-based unobtrusive monitoring of older adults’ frailty. We aim to determine what types of devices comply with unobtrusiveness requirements, which frailty markers have been unobtrusively assessed, which unsupervised devices have been tested, the relationships between sensor outcomes and frailty markers, and which devices can assess multiple markers. SCOPUS, PUBMED, and Web of Science were used to identify papers published 2010–2020. We selected 67 documents involving non-hospitalized older adults (65+ y.o.) and assessing frailty level or some specific frailty-marker with some sensor. Among the nine types of body worn sensors, only inertial measurement units (IMUs) on the waist and wrist-worn sensors comply with ubiquity. The former can transparently assess all variables but weight loss. Wrist-worn devices have not been tested in unsupervised conditions. Unsupervised presence detectors can predict frailty, slowness, performance, and physical activity. Waist IMUs and presence detectors are the most promising candidates for unobtrusive and unsupervised monitoring of frailty. Further research is necessary to give specific predictions of frailty level with unsupervised waist IMUs.

Effect of Workstation Type on the Relationship Between Fatigue, Physical Activity, Stress, and Sleep

OBJECTIVE

This study examined office workstation types' impact on the relationship between fatigue and three health metrics: physical activity, stress, and sleep quality.

METHODS

Data from 225 office workers were collected for perceived fatigue, perceived sleep quality (Pittsburgh Sleep Quality Index [PSQI]), physiological stress response (standard deviation of heart rate variability [HRV]), and physical activity (total activity in minutes) during three consecutive workdays. Stress and physical activity were measured using chest-worn sensors. Workers were then categorized as tired or not-tired based on the median of the fatigue rating.

RESULTS

Among tired workers, open-bench seating workers had increased physical activity, improved sleep quality, and reduced stress compared with workers in private offices and cubicles.

CONCLUSIONS

Office workstation types influence physical activity and levels of stress during work hours, which in turn affect sleep quality.

Machine Learning-Based Physical Activity Tracking with a view to Frailty Analysis

Frailty in old age is defined as the individual intrinsic susceptibility of having bad outcomes following a health problem. It relies on sarcopenia, mobility and activity. Recognizing and monitoring a range of physical activities is a necessary step which precedes the analysis of this syndrome. This paper investigates the optimal tools for this recognition in terms of type and placement of wearable sensors. Two machine learning procedures are proposed and compared on a public dataset. The first one is based on deep learning, where feature extraction is done manually, by constructing activity images from raw signals and applying convolutional neural networks to learn optimal features from these images. The second one is based on shallow learning, where hundreds of handcrafted features are extracted manually, followed by a novel feature selection approach to retain the most discriminant subset.Clinical relevance- This analysis is an indispensable prerequisite to develop efficacious way in order to identify people with frailty using sensors and moreover, to take on the challenge of frailty prevention, an actual world health organization priority.

Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study

Background

Frailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0% to 59.1%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population.

Objective

The objective of this study was to prove that using a wearable device for assessing frailty in older home care clients could be possible.

Methods

From June 2018 to September 2019, we recruited home care clients aged 55 years and older to be monitored over a minimum of 8 days using a wearable device. Detailed sociodemographic information and patient assessments including degree of comorbidity and activities of daily living were collected. Frailty was measured using the Fried Frailty Index. Data collected from the wearable device were used to derive variables including daily step count, total sleep time, deep sleep time, light sleep time, awake time, sleep quality, heart rate, and heart rate standard deviation. Using both wearable and conventional assessment data, multiple logistic regression models were fitted via a sequential stepwise feature selection to predict frailty.

Results

A total of 37 older home care clients completed the study. The mean age was 82.27 (SD 10.84) years, and 76% (28/37) were female; 13 participants were frail, significantly older (P<.01), utilized more home care service (P=.01), walked less (P=.04), slept longer (P=.01), and had longer deep sleep time (P<.01). Total sleep time (r=0.41, P=.01) and deep sleep time (r=0.53, P<.01) were moderately correlated with frailty. The logistic regression model fitted with deep sleep time, step count, age, and education level yielded the best predictive performance with an area under the receiver operating characteristics curve value of 0.90 (Hosmer-Lemeshow P=.88).

Conclusions

We proved that a wearable device could be used to assess frailty for older home care clients. Wearable data complemented the existing assessments and enhanced predictive power. Wearable technology can be used to identify vulnerable older adults who may benefit from additional home care services.

The effect of vibratory stimulation on the timed-up-and-go mobility test: a pilot study for sensory-related fall risk assessment

Effects of localized lower-extremity vibration on postural balance have been reported. The purpose of the current study was to investigate the effect of low-frequency vibration of calf muscles on the instrumented Timed-Up-and-Go (iTUG) test among older adults. Older adults were recruited and classified to low (n=10, age=72.9±2.8 years) and high fall risk (n=10, age=83.6±9.6) using STEADI. Vibratory system (30Hz or 40Hz), was positioned on calves along with wearable motion sensors. Participants performed the iTUG test three times, under conditions of no-vibration, 30Hz, and 40Hz vibration. Percentage differences in duration of iTUG components were calculated comparing vibration vs no-vibration conditions. Significant between-group differences were observed in iTUG (p=0.03); high fall risk participants showed reduction in the duration of turning (-10 % with 30Hz; p=0.15 and -15 % with 40Hz; p=0.03) and turning and sitting (-18 % with 30Hz; p=0.02 and -10 % with 40Hz; p=0.08). However, vibration increased turning (+18 % with 30Hz; p=0.20 and +27 % with 40Hz; p=0.12) and turning and sitting duration (+27 % with 30Hz; p=0.11 and +47 % with 40Hz; p=0.12) in low fall risk participants. Findings suggest that lower-extremity vibration affects dynamic balance; however, the level of this influence may differ between low and high fall risk older adults, which can potentially be used for assessing aging-related sensory deficits.

Harnessing digital health to objectively assess cognitive impairment in people undergoing hemodialysis process: The Impact of cognitive impairment on mobility performance measured by wearables

Cognitive impairment is prevalent but still poorly diagnosed in hemodialysis adults, mainly because of the impracticality of current tools. This study examined whether remotely monitoring mobility performance can help identifying digital measures of cognitive impairment in hemodialysis patients. Sixty-nine diabetes mellitus hemodialysis patients (age = 64.1±8.1years, body mass index = 31.7±7.6kg/m2) were recruited. According to the Mini-Mental State Exam, 44 (64%) were determined as cognitive-intact, and 25 (36%) as cognitive-impaired. Mobility performance, including cumulated posture duration (sitting, lying, standing, and walking), daily walking performance (step and unbroken walking bout), as well as postural-transition (daily number and average duration), were measured using a validated pendant-sensor for a continuous period of 24-hour during a non-dialysis day. Motor capacity was quantified by assessing standing balance and gait performance under single-task and dual-task conditions. No between-group difference was observed for the motor capacity. However, the mobility performance was different between groups. The cognitive-impaired group spent significantly higher percentage of time in sitting and lying (Cohens effect size d = 0.78, p = 0.005) but took significantly less daily steps (d = 0.69, p = 0.015) than the cognitive-intact group. The largest effect of reduction in number of postural-transition was observed in walk-to-sit transition (d = 0.65, p = 0.020). Regression models based on demographics, addition of daily walking performance, and addition of other mobility performance metrics, led to area-under-curves of 0.76, 0.78, and 0.93, respectively, for discriminating cognitive-impaired cases. This study suggests that mobility performance metrics could be served as potential digital biomarkers of cognitive impairment among hemodialysis patients. It also highlights the additional value of measuring cumulated posture duration and postural-transition to improve the detection of cognitive impairment. Future studies need to examine potential benefits of mobility performance metrics for early diagnosis of cognitive impairment/dementia and timely intervention.

Sensor-Based Daily Physical Activity: Towards Prediction of the Level of Concern about Falling in Peripheral Neuropathy

Concern about falling is prevalent and increases the risk of falling in people with peripheral neuropathy (PN). However, the assessment of concern about falling relies on self-report surveys, and thus continuous monitoring has not been possible. We investigated the influence of concern about falling on sensor-based daily physical activity among people with PN. Forty-nine people with PN and various levels of concern about falling participated in this study. Physical activity outcomes were measured over a period of 48 hours using a validated chest-worn sensor. The level of concern about falling was assessed using the falls efficacy scale-international (FES-I). The low concern group spent approximately 80 min more in walking and approximately 100 min less in sitting/lying compared to the high concern group. In addition, the low concern group had approximately 50% more walking bouts and step counts compared to the high concern group. Across all participants, the duration of walking bouts and total step counts was significantly correlated with FES-I scores. The duration of walking bouts and total step counts may serve as eHealth targets and strategies for fall risk assessment among people with PN.

Validity, reliability, and feasibility of the uSense activity monitor to register physical activity and gait performance in habitual settings of geriatric patients

OBJECTIVE

The aim of the study was to investigate the psychometric quality of a newly developed activity monitor (uSense) to document established physical activity parameters as well as innovative qualitative and quantitative gait characteristics in geriatric patients.

APPROACH

Construct and concurrent validity, test-retest reliability, and feasibility of established as well as innovative characteristics for qualitative gait analysis were analyzed in multi-morbid, geriatric patients with cognitive impairment (CI) (n  =  110), recently discharged from geriatric rehabilitation.

MAIN RESULTS

Spearman correlations of established and innovative uSense parameters reflecting active behavior with clinically relevant construct parameters were on average moderate to high for motor performance and life-space and low to moderate for other parameters, while correlations with uSense parameters reflecting inactive behavior were predominantly low. Concurrent validity of established physical activity parameters showed consistently high correlations between the uSense and an established comparator system (PAMSys^™), but the absolute agreement between both sensor systems was low. On average excellent test-retest reliability for all uSense parameters and good feasibility could be documented.

SIGNIFICANCE

The uSense monitor allows the assessment of established and-for the first time-a semi-qualitative gait assessment of habitual activity behavior in older persons most affected by motor and CI and activity restrictions. On average moderate to good construct validity, high test-retest reliability, and good feasibility indicated a sound psychometric quality of most measures, while the results of concurrent validity as measured by a comparable system indicated high correlation but low absolute agreement based on different algorithms used.

Toward Smart Footwear to Track Frailty Phenotypes-Using Propulsion Performance to Determine Frailty

Frailty assessment is dependent on the availability of trained personnel and it is currently limited to clinic and supervised setting. The growing aging population has made it necessary to find phenotypes of frailty that can be measured in an unsupervised setting for translational application in continuous, remote, and in-place monitoring during daily living activity, such as walking. We analyzed gait performance of 161 older adults using a shin-worn inertial sensor to investigate the feasibility of developing a foot-worn sensor to assess frailty. Sensor-derived gait parameters were extracted and modeled to distinguish different frailty stages, including non-frail, pre-frail, and frail, as determined by Fried Criteria. An artificial neural network model was implemented to evaluate the accuracy of an algorithm using a proposed set of gait parameters in predicting frailty stages. Changes in discriminating power was compared between sensor data extracted from the left and right shin sensor. The aim was to investigate the feasibility of developing a foot-worn sensor to assess frailty. The results yielded a highly accurate model in predicting frailty stages, irrespective of sensor location. The independent predictors of frailty stages were propulsion duration and acceleration, heel-off and toe-off speed, mid stance and mid swing speed, and speed norm. The proposed model enables discriminating different frailty stages with area under curve ranging between 83.2–95.8%. Furthermore, results from the neural network suggest the potential of developing a single-shin worn sensor that would be ideal for unsupervised application and footwear integration for continuous monitoring during walking.

Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study

Background: The geriatric syndrome of frailty is one of the greatest challenges facing the U.S. aging population. Frailty in older adults is associated with higher adverse outcomes, such as mortality and hospitalization. Identifying precise early indicators of pre-frailty and measures of specific frailty components are of key importance to enable targeted interventions and remediation. We hypothesize that sensor-derived parameters, measured by a pendant accelerometer device in the home setting, are sensitive to identifying pre-frailty. Methods: Using the Fried frailty phenotype criteria, 153 community-dwelling, ambulatory older adults were classified as pre-frail (51%), frail (22%), or non-frail (27%). A pendant sensor was used to monitor the at home physical activity, using a chest acceleration over 48 h. An algorithm was developed to quantify physical activity pattern (PAP), physical activity behavior (PAB), and sleep quality parameters. Statistically significant parameters were selected to discriminate the pre-frail from frail and non-frail adults. Results: The stepping parameters, walking parameters, PAB parameters (sedentary and moderate-to-vigorous activity), and the combined parameters reached and area under the curve of 0.87, 0.85, 0.85, and 0.88, respectively, for identifying pre-frail adults. No sleep parameters discriminated the pre-frail from the rest of the adults. Conclusions: This study demonstrates that a pendant sensor can identify pre-frailty via daily home monitoring. These findings may open new opportunities in order to remotely measure and track frailty via telehealth technologies.

Could Wearable and Mobile Technology Improve the Management of Essential Tremor?

Essential tremor (ET) is the most common movement disorder. Individuals exhibit postural and kinetic tremor that worsens over time and patients may also exhibit other motor and non-motor symptoms. While millions of people are affected by this disorder worldwide, several barriers impede an optimal clinical management of symptoms. In this paper, we discuss the impact of ET on patients and review major issues to the optimal management of ET; from the side-effects and limited efficacy of current medical treatments to the limited number of people who seek treatment for their tremor. Then, we propose seven different areas within which mobile and wearable technology may improve the clinical management of ET and review the current state of research in these areas.