A systematic review of balance and fall risk assessments with mobile phone technology

Effects of community-based fall prevention interventions for older adults using information and communication technology: A systematic review and meta-analysis

Objectives: This systematic review and meta-analysis aimed to investigate the effect of fall prevention interventions using information and communication technology (ICT). Methods: A comprehensive search across four databases was performed. The inclusion criteria were fall prevention interventions including telehealth, computerized balance training, exergaming, mobile application education, virtual reality exercise, and cognitive-behavioral training for community-dwelling adults aged ≥60 years. Results: Thirty-four studies were selected. Telehealth, smart home systems, and exergames reduced the risk of falls (RR = 0.63, 95% CI [0.54, 0.75]). Telehealth and exergame improved balance (MD = 3.30, 95% CI [1.91, 4.68]; MD = 4.40, 95% CI [3.09, 5.71]). Telehealth improved physical function (SMD = 0.69, 95% CI [0.23, 1.16]). Overall, ICT fall interventions improved fall efficacy but not cognitive function. For quality of life (QOL), mixed results were found depending on the assessment tools. Conclusion: Future investigations on telehealth, smart home systems, or exergames are needed to motivate older adults to exercise and prevent falls.

Smartphone-based gait and balance assessment in survivors of stroke: a systematic review

PURPOSE

Gait and balance impairments are associated with falls and reduced quality of life among survivors of stroke (SS). Effective methods to assess these impairments at-home and in-clinic can help reduce fall risks and improve functional outcomes. Smartphone technology may be able to evaluate these impairments. This review aims to summarize the validity, reliability, sensitivity, and specificity of smartphone applications for determining gait and balance disorders in SS.

METHOD

Database search through PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss was conducted to retrieve studies that explored the use of smartphone-based applications for assessing gait and balance disorders in SS. Two independent reviewers screened potential articles to determine eligibility for inclusion. Eligible studies were summarized for participant and study characteristics, validity, reliability, sensitivity, and specificity of smartphone assessments. Methodological quality assessment of studies was performed using the NIH Quality Assessment Tool.

RESULTS

Seven cross-sectional studies were included in the review. Quality assessment revealed all studies had low risk of bias. Three of the included studies examined the validity, four examined the reliability, and two examined the specificity and sensitivity of smartphone-based application assessments of gait and balance in SS. Studies revealed that smartphones were valid, reliable, specific, and sensitive. Six of the seven included studies intended their use for SS and one study for clinicians.

CONCLUSION

Preliminary evidence supports that smartphone-based gait and balance assessments are valid, reliable, sensitive, and specific in SS in laboratory settings. Future research is needed to test smartphone-based gait and balance assessments in home settings and determine optimal wear sites for assessments.IMPLICATIONS FOR REHABILITATIONSmartphone-based gait and balance assessments are feasible, valid and reliable for survivors of strokeThe findings may guide future research to standardize the use of smartphone to assess gait and balance in this population.The remote use of smartphone-based assessments to predict fall risk in survivors of stroke needs to be explored.

The Reliability and Accuracy of a Fall Risk Assessment Procedure Using Mobile Smartphone Sensors Compared with a Physiological Profile Assessment

Falls in older people are a major health concern as the leading cause of disability and the second most common cause of accidental death. We developed a rapid fall risk assessment based on a combination of physical performance measurements made with an inertial sensor embedded in a smartphone. This study aimed to evaluate and validate the reliability and accuracy of an easy-to-use smartphone fall risk assessment by comparing it with the Physiological Profile Assessment (PPA) results. Sixty-five participants older than 55 performed a variation of the Timed Up and Go test using smartphone sensors. Balance and gait parameters were calculated, and their reliability was assessed by the (ICC) and compared with the PPAs. Since the PPA allows classification into six levels of fall risk, the data obtained from the smartphone assessment were categorised into six equivalent levels using different parametric and nonparametric classifier models with neural networks. The F1 score and geometric mean of each model were also calculated. All selected parameters showed ICCs around 0.9. The best classifier, in terms of accuracy, was the nonparametric mixed input data model with a 100% success rate in the classification category. In conclusion, fall risk can be reliably assessed using a simple, fast smartphone protocol that allows accurate fall risk classification among older people and can be a useful screening tool in clinical settings.

Smart Lacelock Sensor for the Balance Assessment of Community-Dwelling Older People

This paper introduces a novel wearable shoe sensor named the Smart Lacelock Sensor. The sensor can be securely attached to the top of a shoe with laces and incorporates a loadcell to measure the force applied by the shoelace, providing valuable information related to ankle movement and foot loading. As the first step towards the automated balance assessment, this paper investigates the correlations between various levels of physical performance measured by the wearable Smart Lacelock Sensor and the SPPB clinical method in community-living older persons. 19 adults (age 76.84 ± 3.45 years), including those with and without recent fall history and SPPB score ranging from 4 to 12, participated in the study. The Smart Lacelock Sensor was attached to both shoes of each participant by skilled research staff, who then led them through the SPPB evaluation. The data obtained from the Smart Lacelock Sensors after the SPPB assessment were used to evaluate the deviation between the SPPB scores assigned by the research staff and the signals generated by the sensors for various participants. Results demonstrate that the standard deviation of the Smart Lacelock Sensor's loadcell response (both feet) for the side-by-side balance testing is significantly correlated (R2 = 0.68) with the SPPB score, demonstrating the capability of the Smart Lacelock Sensor in balance assessment.

Leg Dominance—Surface Stability Interaction: Effects on Postural Control Assessed by Smartphone-Based Accelerometry

The preferential use of one leg over another in performing lower-limb motor tasks (i.e., leg dominance) is considered to be one of the internal risk factors for sports-related lower-limb injuries. The current study aimed to investigate the effects of leg dominance on postural control during unipedal balancing on three different support surfaces with increasing levels of instability: a firm surface, a foam pad, and a multiaxial balance board. In addition, the interaction effect between leg dominance and surface stability was also tested. To this end, a tri-axial accelerometer-based smartphone sensor was placed over the lumbar spine (L5) of 22 young adults (21.5 ± 0.6 years) to record postural accelerations. Sample entropy (SampEn) was applied to acceleration data as a measure of postural sway regularity (i.e., postural control complexity). The results show that leg dominance (p < 0.001) and interaction (p < 0.001) effects emerge in all acceleration directions. Specifically, balancing on the dominant (kicking) leg shows more irregular postural acceleration fluctuations (high SampEn), reflecting a higher postural control efficiency or automaticity than balancing on the non-dominant leg. However, the interaction effects suggest that unipedal balancing training on unstable surfaces is recommended to reduce interlimb differences in neuromuscular control for injury prevention and rehabilitation.

Blood urea nitrogen to creatinine ratio is associated with physical frailty in older-aged Chinese: a cross-sectional study

BACKGROUND

The relationship between the ratio of blood urea nitrogen to creatinine (BUN/Cr) and physical frailty in elderly patients remains unclear. The study aims to investigate the association between the BUN/Cr ratio and physical frailty in the elderly Chinese population.

METHODS

In this cross-sectional analysis, the clinical data of 5213 participants from 2015 were selected from the China Health and Retirement Longitudinal Study (CHARLS). The demographic variables (including age and gender) and health behavior (including smoking and drinking history), anthropometric (including systolic and diastolic blood pressure, waist circumference (WC), etc.), physical performances (i.e., grip strength, repeated chair stands, etc.), and biochemical indicators (i.e., blood urea nitrogen (BUN), creatinine(Cr), total cholesterol (TC), triglycerides (TG), etc.) were measured. The association between the BUN/Cr ratio and physical frailty was analyzed.

RESULTS

After adjusting for potential confounding factors, smooth curve fitting showed a linear relationship between the BUN/Cr ratio and grip strength, a non-linear relationship between the BUN/Cr ratio, and repeated chair-rising time. The fully adjusted linear regression results showed a negative association between the BUN/Cr ratio and grip strength. In the multivariate, piecewise linear regression, when the BUN/Cr ratio was greater than 18.60, the repeated chair-rising time increased with the increase in BUN/Cr ratio (β = 0.046, 95%CI 0.025, 0.066; p < 0.001). However, we did not observe a significant correlation when the BUN/Cr ratio was less than 18.60 (β = -0.007, 95%CI -0.046, 0.032; p = 0.717).

CONCLUSION

This study demonstrated that the BUN/Cr ratio might be associated with physical frailty in older-aged Chinese, and this association requires further investigation.

Smartphones and Threshold-Based Monitoring Methods Effectively Detect Falls Remotely: A Systematic Review

In the US, at least one fall occurs in at least 28.7% of community-dwelling seniors 65 and older each year. Falls had medical costs of USD 51 billion in 2015 and are projected to reach USD 100 billion by 2030. This review aims to discuss the extent of smartphone (SP) usage in fall detection and prevention across a range of care settings. A computerized search was conducted on six electronic databases to investigate the use of remote sensing technology, wireless technology, and other related MeSH terms for detecting and preventing falls. After applying inclusion and exclusion criteria, 44 studies were included. Most of the studies targeted detecting falls, two focused on detecting and preventing falls, and one only looked at preventing falls. Accelerometers were employed in all the experiments for the detection and/or prevention of falls. The most frequent course of action following a fall event was an alarm to the guardian. Numerous studies investigated in this research used accelerometer data analysis, machine learning, and data from previous falls to devise a boundary and increase detection accuracy. SP was found to have potential as a fall detection system but is not widely implemented. Technology-based applications are being developed to protect at-risk individuals from falls, with the objective of providing more effective and efficient interventions than traditional means. Successful healthcare technology implementation requires cooperation between engineers, clinicians, and administrators.

Relationships between selected indices of postural stability and sports performance in elite badminton players: Pilot study

The main aim of this study was to determine the relationships between postural stability and the place in the ranking of badminton players. The study examined 10 elite players from Polish national badminton team. The scope of the study included basic somatic characteristics, such as body height, body weight, BMI, and training experience. A Microgate GYKO inertial sensor system was used to assess the postural stability of athletes. Using Spearman's rank correlation, cause-and-effect relationships between the place in the sports ranking and the analyzed variables characterizing postural stability were recognized. Depending on the distribution and homogeneity of variance, the significance of differences in variables that characterize postural stability between players of different sports skill levels (two groups) was calculated. The Student's t-test or Mann-Whitney's U-test was used for this purpose. In general, the athletes with higher positions on the ranking list presented a higher level of postural stability in both tests, which is also confirmed by the normalized values. However, for all variables of postural stability, no statistically significant correlations with sports ranking were observed. Higher values of Spearman's rank correlation coefficients were found for the test performed in the one-foot standing test compared to the two-foot test. The results obtained indicate that particular attention in badminton training should be paid to the development of the level of postural stability in order to improve sports performance.

iPhone Accelerometry Provides a Sensitive In-Home Assessment of Age-Related Changes in Standing Balance

Remote health monitoring has become increasingly important, especially in aging populations. We aimed to identify tasks that are sensitive to age-related changes in balance during fully remote, at-home balance assessment. Participants were 12 healthy young adults (mean age = 26.08 years, range: 18-33) and 12 healthy older adults (mean age = 67.33 years, range: 60-75). Participants performed standing tasks monitored via video conference while their balance was quantified using a custom iPhone application measuring mediolateral center of mass acceleration. We included three stances (feet together, tandem, and single leg) with eyes open or closed, with or without a concurrent cognitive task. Older adults demonstrated significantly more variable center of mass accelerations in tandem (p = .04, ηp2=.25) and significantly higher (p < .01, ηp2=.45) and more variable (p < .01, ηp2=.44) center of mass accelerations in single leg compared with young adults. We also observed that as task challenge increased, balance dual-task cost diminished for older, but not young, adults.

Patterns and predictors of fall injury transitions among Korean older adult fallers: a 2-year longitudinal study

This study was conducted to identify fall injury patterns, the transition from the baseline to follow-up, and the factors associated with the identified fall injury patterns using data obtained from the Korean Frailty and Aging Cohort Study. The participants were 566 community-dwelling older adults with fall experience. Three fall injury patterns were identified as the baseline and follow-up periods. The probability that the participant in the "fracture injury" pattern at Time 1 transitioned to the "fracture injury" pattern at Time 2 was 0.098. The factors associated with the "bruising and/or sprain injury" pattern were education level (relative risk ratio [RRR] = 0.55, p = 0.012), alcohol consumption (RRR = 0.50, p = 0.034), and balancing in tandem position (RRR = 2.77, p < 0.001). In the "fracture injury" pattern, male (RRR = 0.22, p = 0.038), frailty score (RRR = 0.58, p = 0.042), "bruising injury" (RRR = 0.23, p = 0.007), and "sprain injury" (RRR = 0.20, p = 0.007) at the baseline were significant factors. The findings indicate that previous fall experiences, higher alcohol consumption, lower frailty scores, and poor balance levels are associated with fall injury patterns. These patterns should be considered when developing prevention interventions.

Neuromotor changes in participants with a concussion history can be detected with a custom smartphone app

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between concussed and non-concussed participants. Data were collected at two university laboratories and two military sites. Participants included civilians and Service Members (N = 216) with and without a clinically diagnosed concussion. Kinematic and variability metrics were derived from a thigh angle time series while the participants completed a series of stepping-in-place tasks in three conditions: eyes open, eyes closed, and head shake. We observed that the standard deviation of the mean maximum angular velocity of the thigh was higher in the participants with a concussion history in the eyes closed and head shake conditions of the stepping-in-place task. Consistent with the optimal movement variability hypothesis, we showed that increased movement variability occurs in participants with a concussion history, for which our smartphone app and protocol were sensitive enough to capture.

The Usability of a Smartphone-Based Fall Risk Assessment App for Adult Wheelchair Users: Observational Study

Background

Individuals who use wheelchairs and scooters rarely undergo fall risk screening. Mobile health technology is a possible avenue to provide fall risk assessment. The promise of this approach is dependent upon its usability.

Objective

We aimed to determine the usability of a fall risk mobile health app and identify key technology development insights for aging adults who use wheeled devices.

Methods

Two rounds (with 5 participants in each round) of usability testing utilizing an iterative design-evaluation process were performed. Participants completed use of the custom-designed fall risk app, Steady-Wheels. To quantify fall risk, the app led participants through 12 demographic questions and 3 progressively more challenging seated balance tasks. Once completed, participants shared insights on the app’s usability through semistructured interviews and completion of the Systematic Usability Scale. Testing sessions were recorded and transcribed. Codes were identified within the transcriptions to create themes. Average Systematic Usability Scale scores were calculated for each round.

Results

The first round of testing yielded 2 main themes: ease of use and flexibility of design. Systematic Usability Scale scores ranged from 72.5 to 97.5 with a mean score of 84.5 (SD 11.4). After modifications were made, the second round of testing yielded 2 new themes: app layout and clarity of instruction. Systematic Usability Scale scores improved in the second iteration and ranged from 87.5 to 97.5 with a mean score of 91.9 (SD 4.3).

Conclusions

The mobile health app, Steady-Wheels, has excellent usability and the potential to provide adult wheeled device users with an easy-to-use, remote fall risk assessment tool. Characteristics that promoted usability were guided navigation, large text and radio buttons, clear and brief instructions accompanied by representative illustrations, and simple error recovery. Intuitive fall risk reporting was achieved through the presentation of a single number located on a color-coordinated continuum that delineated low, medium, and high risk.

Validity and reliability of a smartphone-based assessment for anticipatory and compensatory postural adjustments during predictable perturbations

BACKGROUND

Postural adjustments involve displacements of the center of mass (COM), controlled by the central nervous system (CNS), to maintain equilibrium whilst standing. Postural adjustments can be anticipatory (APAs) or compensatory (CPAs), and are triggered to counteract predictable perturbations.

RESEARCH QUESTION

Is the new smartphone application, Momentum, a valid and reliable tool for the assessment of body balance, by measuring APAs and CPAs using accelerometer readings?

METHODS

20 young adults were exposed to external predictable perturbations induced at the shoulder level, whilst standing. COM linear acceleration was recorded by Momentum (extracting data from a smartphone's accelerometer) and a 3D motion capture system.

RESULTS

The key results demonstrated a very high, significant correlation (r ≥ 0.7, p < 0.05) between the two device settings in the APA parameters_, which obtained r = 0.65, denoting a high correlation. Considering the reliability, variables that are compensatory in nature are presented on a scale of good to excellent in measurement methods, kinematics, and Momentum. However, the anticipatory variables presented excellent reliability only for the kinematics.

SIGNIFICANCE

These experiments show that Momentum is a valid method for measuring COM acceleration under predictable perturbations and is reliable for compensatory events.

Wearable Devices and Smartphone Inertial Sensors for Static Balance Assessment: A Concurrent Validity Study in Young Adult Population

Falls represent a public health issue around the world and prevention is an important part of the politics of many countries. The standard method of evaluating balance is posturography using a force platform, which has high financial costs. Other instruments, such as portable devices and smartphones, have been evaluated as low-cost alternatives to the screening of balance control. Although smartphones and wearables have different sizes, shapes, and weights, they have been systematically validated for static balance control tasks. Different studies have applied different experimental configurations to validate the inertial measurements obtained by these devices. We aim to evaluate the concurrent validity of a smartphone and a portable device for the evaluation of static balance control in the same group of participants. Twenty-six healthy and young subjects comprised the sample. The validity for static balance control evaluation of built-in accelerometers inside portable smartphone and wearable devices was tested considering force platform recordings as a gold standard for comparisons. A linear correlation (r) between the quantitative variables obtained from the inertial sensors and the force platform was used as an indicator of the concurrent validity. Reliability of the measures was calculated using Intraclass correlation in a subsample (n = 14). Smartphones had 11 out of 12 variables with significant moderate to very high correlation (r > 0.5, p < 0.05) with force platform variables in open eyes, closed eyes, and unipedal conditions, while wearable devices had 8 out of 12 variables with moderate to very high correlation (r > 0.5, p < 0.05) with force platform variables under the same task conditions. Significant reliabilities were found in closed eye conditions for smartphones and wearables. The smartphone and wearable devices had concurrent validity for the static balance evaluation and the smartphone had better validity results than the wearables for the static balance evaluation.

Successful 10-second one-legged stance performance predicts survival in middle-aged and older individuals

OBJECTIVES

Balance quickly diminishes after the mid-50s increasing the risk for falls and other adverse health outcomes. Our aim was to assess whether the ability to complete a 10- s one-legged stance (10-second OLS) is associated with all-cause mortality and whether it adds relevant prognostic information beyond ordinary demographic, anthropometric and clinical data.

METHODS

Anthropometric, clinical and vital status and 10-s OLS data were assessed in 1702 individuals (68% men) aged 51-75 years between 2008 and 2020. Log-rank and Cox modelling were used to compare survival curves and risk of death according to ability (YES) or inability (NO) to complete the 10-s OLS test.

RESULTS

Overall, 20.4% of the individuals were classified as NO. During a median follow-up of 7 years, 7.2% died, with 4.6% (YES) and 17.5% (NO) on the 10-s OLS. Survival curves were worse for NO 10-s OLS (log-rank test=85.6; p<0.001). In an adjusted model incorporating age, sex, body mass index and comorbidities, the HR of all-cause mortality was higher (1.84 (95% CI: 1.23 to 2.78) (p<0.001)) for NO individuals. Adding 10-s OLS to a model containing established risk factors was associated with significantly improved mortality risk prediction as measured by differences in -2 log likelihood and integrated discrimination improvement.

CONCLUSIONS

Within the limitations of uncontrolled variables such as recent history of falls and physical activity, the ability to successfully complete the 10-s OLS is independently associated with all-cause mortality and adds relevant prognostic information beyond age, sex and several other anthropometric and clinical variables. There is potential benefit to including the 10-s OLS as part of routine physical examination in middle-aged and older adults.

Mobile Technology for Falls Prevention in Older Adults

Falls are the leading cause of accidental death in older adults that result from a complex interplay of risk factors. Recently, the need for person-centered approach utilizing personalization, prediction, prevention and participation, known as the P4 model, in fall prevention has been highlighted. Features of mobile technology make it a suitable technological infrastructure to employ such an approach. This narrative review aims to review the evidence for using mobile technology for personalized fall risk assessment and prevention since 2017 in older adults. We aim to identify lessons learned and future directions for using mobile technology as a fall risk assessment and prevention tool. Articles were searched in PubMed and Web of Science with search terms related to older adults, mobile technology, and falls prevention. A total of 23 articles were included. Articles were identified as those examining aspects of the P4 model including prediction (measurement of fall risk), personalization (usability), prevention, and participation. Mobile technology appears to be comparable to gold-standard technology in measuring well-known fall risk factors including static and dynamic balance. Seven applications were developed to measure different fall risk factors and tested for personalization, and/or participation aspects, and four were integrated into a falls prevention program. Mobile health technology offers an innovative solution to provide tailored fall risk screening, prediction, and participation. Future studies should incorporate multiple, objective fall risk measures and implement them in community settings to determine if mobile technology can offer tailored and scalable interventions.

Validity and Reliability of Smartphone App for Evaluating Postural Adjustments during Step Initiation

The evaluation of anticipatory postural adjustments (APAs) requires high-cost and complex handling systems, only available at research laboratories. New alternative methods are being developed in this field, on the other hand, to solve this issue and allow applicability in clinic, sport and hospital environments. The objective of this study was to validate an app for mobile devices to measure the APAs during gait initiation by comparing the signals obtained from cell phones using the Momentum app with measurements made by a kinematic system. The center-of-mass accelerations of a total of 20 healthy subjects were measured by the above app, which read the inertial sensors of the smartphones, and by kinematics, with a reflective marker positioned on their lumbar spine. The subjects took a step forward after hearing a command from an experimenter. The variables of the anticipatory phase, prior to the heel-off and the step phase, were measured. In the anticipatory phase, the linear correlation of all variables measured by the two measurement techniques was significant and indicated a high correlation between the devices (APAonset: r = 0.95, p < 0.0001; APAamp: r = 0.71, p = 0.003, and PEAKtime: r = 0.95, p < 0.0001). The linear correlation between the two measurement techniques for the step phase variables measured by ques was also significant (STEPinterval: r = 0.56, p = 0.008; STEPpeak1: r = 0.79, p < 0.0001; and STEPpeak2: r = 0.64, p < 0.0001). The Bland−Altman graphs indicated agreement between instruments with similar behavior as well as subjects within confidence limits and low dispersion. Thus, using the Momentum cell phone application is valid for the assessment of APAs during gait initiation compared to the gold standard instrument (kinematics), proving to be a useful, less complex, and less costly alternative for the assessment of healthy individuals.

Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders

The understanding of locomotion in neurological disorders requires technologies for quantitative gait analysis. Numerous modalities are available today to objectively capture spatiotemporal gait and postural control features. Nevertheless, many obstacles prevent the application of these technologies to their full potential in neurological research and especially clinical practice. These include the required expert knowledge, time for data collection, and missing standards for data analysis and reporting. Here, we provide a technological review of wearable and vision-based portable motion analysis tools that emerged in the last decade with recent applications in neurological disorders such as Parkinson's disease and Multiple Sclerosis. The goal is to enable the reader to understand the available technologies with their individual strengths and limitations in order to make an informed decision for own investigations and clinical applications. We foresee that ongoing developments toward user-friendly automated devices will allow for closed-loop applications, long-term monitoring, and telemedical consulting in real-life environments.

The Context of Caring and Concern for Falling Differentiate Which Mobile Fall Technology Features Chinese Family Caregivers Find Most Important

Falls are not only a leading cause of death and disability, but also a strain on the capacity for caregivers to provide care. This study examined how the context of caregiving relates to the importance of caregiver-defined mobile fall prevention feature sets. A sample of 266 family caregivers, recruited from a Chinese social media platform, reported care for an older adult and interest in mobile fall prevention technology features. Factor analysis identified three caregiver-defined feature sets: automatic fall response, digitized fall prevention tools, and social features. Multiple regression showed caregivers' concern about falling was the most robust predictor of a feature set's importance. Poisson regression revealed that caregiver concern and assistance with instrumental activities of daily living were associated with rating more features as important. Our findings suggest that caregivers are interested in mobile fall prevention technologies that support older adults' independence while also alleviating concerns about falling.

FallSkip device is a useful tool for fall risk assessment in sarcopenic older community people

PURPOSE

Fall prevention is a major health concern for the ageing population. Sarcopenia is considered a risk factor for falls. Some instruments, such as Time Up and Go (TUG), are used for screening risk. The use of sensors has also been shown to be a viable tool that can provide accurate, cost-effective, and easy to manage assessment of fall risk. One novel sensor for assessing fall risk in older people is the Fallskip device. The present study evaluates the performance of the FallSkip device against the TUG method in fall risk screening and assesses its measurement properties in sarcopenic older people.

METHODS

A cross-sectional study was made in a sample of community-dwelling sarcopenic and non-sarcopenic older people aged 70 years or over.

RESULTS

The study sample consisted of 34 older people with a mean age of 77.03 (6.58) years, of which 79.4% (n = 27) were females, and 41.2% (n = 14) were sarcopenic. The Pearson correlation coefficient between TUG time and FallSkip time was 0.70 (p < 0.001). The sarcopenic individuals took longer in performing both TUG and FallSkip. They also presented poorer reaction time, gait and sit-to-stand - though no statistically significant differences were observed. The results in terms of feasibility, acceptability, reliability and validity in sarcopenic older people with FallSkip were acceptable.

CONCLUSIONS

The FallSkip device has suitable metric properties for the assessment of fall risk in sarcopenic community-dwelling older people. FallSkip analyses more parameters than TUG in assessing fall risk and has greater discriminatory power in evaluating the risk of falls.

Balance provocation tests identify near falls in healthy community adults aged 40-75 years; an observational study

BACKGROUND

Near falls, such as stumbles or slips without falling to the ground, are more common than falls and often lead to a fall.

PURPOSE

The objective of this study was to investigate which balance tests differentiate near fallers from fallers and non-fallers.

METHODS

This cross-sectional, observational study assessed balance in healthy community dwelling adults aged 40-75 years. Participants reported falls and near falls in the previous 6 months. Balance testing was completed in the local community for static (i.e. feet together and single-leg stance) and dynamic balance (i.e. tandem walk, Functional Movement Screen hurdle step and lunge). Between-group comparative analysis of pass-fail for each balance test was undertaken.

RESULTS

Of 627 participants, there were 99 fallers (15.8%), 121 near fallers (19.3%) and 407 non-fallers (64.9%). Near fallers were twice as likely as non-fallers to fail single-leg stance eyes (OR 2.7, 95% CI 1.5-4.9), five tandem steps (OR 2.5, 95% CI 1.5-5.7), hurdle step (OR 2.9, 95% CI 1.4-5.8), and lunge (OR 2.5. 95% CI 1.5-4.1). The predictive capacity differentiates near fallers with a sensitivity of 73.3%.

DISCUSSION

A new battery of tests assessing static and dynamic balance identifies near fallers in seemingly healthy, community dwelling middle- and young-older-aged adults.

Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review

Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals’ motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.

Gait and Balance Assessments using Smartphone Applications in Parkinson's Disease: A Systematic Review

Gait dysfunctions and balance impairments are key fall risk factors and associated with reduced quality of life in individuals with Parkinson's Disease (PD). Smartphone-based assessments show potential to increase remote monitoring of the disease. This review aimed to summarize the validity, reliability, and discriminative abilities of smartphone applications to assess gait, balance, and falls in PD. Two independent reviewers screened articles systematically identified through PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss. Studies that used smartphone-based gait, balance, or fall applications in PD were retrieved. The validity, reliability, and discriminative abilities of the smartphone applications were summarized and qualitatively discussed. Methodological quality appraisal of the studies was performed using the quality assessment tool for observational cohort and cross-sectional studies. Thirty-one articles were included in this review. The studies present mostly with low risk of bias. In total, 52% of the studies reported validity, 22% reported reliability, and 55% reported discriminative abilities of smartphone applications to evaluate gait, balance, and falls in PD. Those studies reported strong validity, good to excellent reliability, and good discriminative properties of smartphone applications. Only 19% of the studies formally evaluated the usability of their smartphone applications. The current evidence supports the use of smartphone to assess gait and balance, and detect freezing of gait in PD. More studies are needed to explore the use of smartphone to predict falls in this population. Further studies are also warranted to evaluate the usability of smartphone applications to improve remote monitoring in this population.Registration: PROSPERO CRD 42020198510.

Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review

Compared to laboratory equipment inertial sensors are inexpensive and portable, permitting the measurement of postural sway and balance to be conducted in any setting. This systematic review investigated the inter-sensor and test-retest reliability, and concurrent and discriminant validity to measure static and dynamic balance in healthy adults. Medline, PubMed, Embase, Scopus, CINAHL, and Web of Science were searched to January 2021. Nineteen studies met the inclusion criteria. Meta-analysis was possible for reliability studies only and it was found that inertial sensors are reliable to measure static standing eyes open. A synthesis of the included studies shows moderate to good reliability for dynamic balance. Concurrent validity is moderate for both static and dynamic balance. Sensors discriminate old from young adults by amplitude of mediolateral sway, gait velocity, step length, and turn speed. Fallers are discriminated from non-fallers by sensor measures during walking, stepping, and sit to stand. The accuracy of discrimination is unable to be determined conclusively. Using inertial sensors to measure postural sway in healthy adults provides real-time data collected in the natural environment and enables discrimination between fallers and non-fallers. The ability of inertial sensors to identify differences in postural sway components related to altered performance in clinical tests can inform targeted interventions for the prevention of falls and near falls.

Unsupervised Assessment of Balance and Falls Risk Using a Smartphone and Machine Learning

Assessment of health and physical function using smartphones (mHealth) has enormous potential due to the ubiquity of smartphones and their potential to provide low cost, scalable access to care as well as frequent, objective measurements, outside of clinical environments. Validation of the algorithms and outcome measures used by mHealth apps is of paramount importance, as poorly validated apps have been found to be harmful to patients. Falls are a complex, common and costly problem in the older adult population. Deficits in balance and postural control are strongly associated with falls risk. Assessment of balance and falls risk using a validated smartphone app may lessen the need for clinical assessments which can be expensive, requiring non-portable equipment and specialist expertise. This study reports results for the real-world deployment of a smartphone app for self-directed, unsupervised assessment of balance and falls risk. The app relies on a previously validated algorithm for assessment of balance and falls risk; the outcome measures employed were trained prior to deployment on an independent data set. Results for a sample of 594 smartphone assessments from 147 unique phones show a strong association between self-reported falls history and the falls risk and balance impairment scores produced by the app, suggesting they may be clinically useful outcome measures. In addition, analysis of the quantitative balance features produced seems to suggest that unsupervised, self-directed assessment of balance in the home is feasible.

Development and use of mobile messaging for individuals with musculoskeletal pain conditions: a scoping review protocol

INTRODUCTION

Previous reviews of mobile messaging for individuals with musculoskeletal pain have shown positive effects on pain and disability. However, the configuration of digital content, method of presentation and interaction, dose and frequency needed for optimal results remain unclear. Patient preferences concerning such systems are also unclear. Addressing these knowledge gaps, incorporating evidence from both experimental and observational studies, may be useful to understand the extent of the relevant literature, and to influence the design and outcomes of future messaging systems. We aim to map information that could be influential in the design of future mobile messaging systems for individuals with musculoskeletal pain conditions, and to summarise the findings of efficacy, effectiveness, and economics derived from both experimental and observational studies.

METHODS AND ANALYSIS

We will include studies describing the development and/or use of mobile messaging to support adults (≥18 years) with acute or chronic musculoskeletal pain. We will exclude digital health studies that lack a mobile messaging component, or those targeted at other health conditions unrelated to the bones, muscles and connective tissues, or involving surgical or patients with cancer, or studies involving solely healthy individuals. Our sources of information will be online databases and reference lists of relevant papers. We will include papers published in English in the last 10 years. Two pairs of independent reviewers will screen, select and extract the data, with any disagreements mediated by a third reviewer. We will report the results according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews checklist. We will synthesise the findings in a tabular format and provide a descriptive summary.

ETHICS AND DISSEMINATION

Formal ethical approval is not required. We will disseminate the findings through publication in a peer-reviewed journal, relevant conferences, and relevant consumer forums.

TRIAL REGISTRATION

Open Science Framework https://osf.io/8mzya; DOI: 10.17605/OSF.IO/8MZYA.

The negative impact of smartphone usage on nursing students: An integrative literature review

BACKGROUND

Smartphones are ubiquitous, and for some, an indispensable companion. In nursing education curricula and clinical healthcare settings, smartphones have the potential to augment student learning. Nursing students report significant benefits to smartphone use, which extend beyond learning, to include enhanced communication, clinical decision making and evidence-based practice. Despite these benefits, little is known about the negative impact of smartphones on student learning.

OBJECTIVES

This integrative review aimed to synthesise findings from published research that referred to the detrimental direct or indirect effect of smartphone usage on nursing students.

DESIGN

The integrative review was guided by the five-stage approach as conceptualised by Whittemore and Knafl (2005).

METHODS

Seven electronic databases were systematically searched in consultation with a university librarian (CINAHL Plus, Ovid Medline ALL, Nursing and Allied Health Database, PsycINFO, PubMed, Scopus and ERIC) using a combination of key search terms and medical subject headings. A total of 646 articles were retrieved, and following removal of duplicates, screening of titles and abstracts, a final 27 articles met the inclusion criteria for this review.

RESULTS

Studies in the review originated from Korea (n = 7), Turkey (n = 6), India (n = 4), Spain (n = 3), USA (n = 2), Spain/Portugal (n = 1), Iran (n = 1), France (n = 1), Canada (n = 1) and Egypt (n = 1). Personal smartphone use was reported to be a distraction within clinical and classroom learning, and considered as uncivil, and compromised professionalism. Frequently, smartphones were used for entertainment (e.g. social networking) rather than professional purposes. The studies identified a concerning level of nomophobia and smartphone addiction among nursing students that caused stress and anxiety, and adversely affected sleep, learning and academic performance. Recommendations were proposed for smartphone policies.

CONCLUSIONS

Excessive smartphones use among nursing students may adversely affect physical and mental health and potentially impact on student learning within the classroom and clinical environment. Educators should consider the implementation of policies or guidance for the responsible use of smartphones by nursing students whilst in the classroom setting and during clinical placement, to mitigate the potential negative impact on health and academic performance.

Smartphone applications to assess gait and postural control in people with multiple sclerosis: A systematic review

BACKGROUND

Methods to effectively assess gait and balance impairments are necessary to guide interventions among people with Multiple Sclerosis (PwMS). Smartphone-based evaluations are becoming popular due to the ubiquitous use of smartphones in society.

OBJECTIVE

To determine the current state of smartphone applications that assess gait and balance among PwMS.

METHODS

Two independent reviewers screened articles retrieved from PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss. Articles meeting eligibility criteria were summarized and qualitatively discussed. Participant characteristics, validity, reliability, sensitivity and specificity measures, and main results of smartphone-based gait and balance evaluations were summarized. Methodological quality appraisal of the studies was performed using the quality assessment tool for observational cohort and cross-sectional studies.

RESULTS

Eight articles were included in this review. The studies present mostly with low risk of bias. All studies successfully tested the use of smartphone applications in assessing gait and balance among PwMS. In total, 75% of the studies evaluated the validity; 38% evaluated the reliability, sensitivity, and specificity of smartphone applications to assess gait and balance. Of those, all studies except one found smartphone applications to be appropriately valid, reliable, sensitive, and specific in assessing gait and balance. Most studies (88%) reported PwMS and clinicians as their intended users.

CONCLUSION

There is evidence supporting the use of smartphone applications to assess gait and balance among PwMS. Future studies should further examine the psychometric properties of smartphone-based gait and postural control assessments as well as the sensitivity and specificity to improve the interpretation of the results.

Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study

BACKGROUND

Multiple sclerosis (MS) is a chronic, neurodegenerative disease that causes a range of motor, sensory, and cognitive symptoms. Due to these symptoms, people with MS are at a high risk for falls, fall-related injuries, and reductions in quality of life. There is no cure for MS, and managing symptoms and disease progression is important to maintain a high quality of life. Mobile health (mHealth) apps are commonly used by people with MS to help manage their health. However, there are limited health apps for people with MS designed to evaluate fall risk. A fall risk app can increase access to fall risk assessments and improve self-management. When designing mHealth apps, a user-centered approach is critical for improving use and adoption.

OBJECTIVE

The purpose of this study is to undergo a user-centered approach to test and refine the usability of the app through an iterative design process.

METHODS

The fall risk app Steady-MS is an extension of Steady, a fall risk app for older adults. Steady-MS consists of 2 components: a 25-item questionnaire about demographics and MS symptoms and 5 standing balance tasks. Data from the questionnaire and balance tasks were inputted into an algorithm to compute a fall risk score. Two iterations of semistructured interviews (n=5 participants per iteration) were performed to evaluate usability. People with MS used Steady-MS on a smartphone, thinking out loud. Interviews were recorded, transcribed, and developed into codes and themes. People with MS also completed the System Usability Scale.

RESULTS

A total of 3 themes were identified: intuitive navigation, efficiency of use, and perceived value. Overall, the participants found Steady-MS efficient to use and useful to learn their fall risk score. There were challenges related to cognitive overload during the balance tasks. Modifications were made, and after the second iteration, people with MS reported that the app was intuitive and efficient. Average System Usability Scale scores were 95.5 in both iterations, representing excellent usability.

CONCLUSIONS

Steady-MS is the first mHealth app for people with MS to assess their overall risk of falling and is usable by a subset of people with MS. People with MS found Steady-MS to be usable and useful for understanding their risk of falling. When developing future mHealth apps for people with MS, it is important to prevent cognitive overload through simple and clear instructions and present scores that are understood and interpreted correctly through visuals and text. These findings underscore the importance of user-centered design and provide a foundation for the future development of tools to assess and prevent scalable falls for people with MS. Future steps include understanding the validity of the fall risk algorithm and evaluating the clinical utility of the app.

Evaluation of Concurrent Validity between a Smartphone Self-Test Prototype and Clinical Instruments for Balance and Leg Strength

The evolving use of sensors to objectively assess movements is a potentially valuable addition to clinical assessments. We have developed a new self-test application prototype, MyBalance, in the context of fall prevention aimed for use by older adults in order to independently assess balance and functional leg strength. The objective of this study was to investigate the new self-test application for concurrent validity between clinical instruments and variables collected with a smartphone. The prototype has two test procedures: static standing balance test in two positions, and leg strength test performed as a sit-to-stand test. Thirty-one older adults were assessed for balance and functional leg strength, in an outpatient physiotherapy setting, using seven different clinical assessments and three sensor-tests. The results show that clinical instruments and sensor measurements correlate to a higher degree for the smartphone leg strength test. For balance tests, only a few moderate correlations were seen in the Feet Together position and no significant correlations for the Semi Tandem Stance. This study served as a first step to develop a smartphone self-test application for older adults to assess functional balance at home. Further research is needed to test validity, reliability, and user-experience of this new self-test application.

Validation of a smartphone embedded inertial measurement unit for measuring postural stability in older adults

BACKGROUND

Identifying older adults with increased fall risk due to poor postural control on a large scale is only possible through omnipresent and low cost measuring devices such as the inertial measurement units (IMU) embedded in smartphones. However, the correlation between smartphone measures of postural stability and state-of-the-art force plate measures has never been assessed in a large sample allowing us to take into account age as a covariate.

RESEARCH QUESTION

How reliably can postural stability be measured with a smartphone embedded IMU in comparison to a force plate?

METHODS

We assessed balance in 97 adults aged 50-90 years in four different conditions (eyes open, eyes closed, semi-tandem and dual-task) in the anterio-posterior and medio-lateral directions. We used six different parameters (root mean square and average absolute value of COP displacement, velocity and acceleration) for the force plate and two different parameters (root mean square and average absolute value of COM acceleration) for the smartphone.

RESULTS

Test-retest reliability was smaller for the smartphone than for the force plate (intra class correlation) but both devices could equally well detect differences between conditions (similar Cohen's d). Parameters from the smartphone and the force plate, with age regressed out, were moderately correlated (robust correlation coefficients of around 0.5).

SIGNIFICANCE

This study comprehensively documents test-retest reliability and effect sizes for stability measures obtained with a force plate and smartphone as well as correlations between force plate and smartphone measures based on a large sample of older adults. Our large sample size allowed us to reliably determine the strength of the correlations between force plate and smartphone measures. The most important practical implication of our results is that more repetitions or longer trials are required when using a smartphone instead of a force plate to assess balance.

Smartphone accelerometry to assess postural control in individuals with multiple sclerosis

BACKGROUND

Falls are a major health concern for people with Multiple Sclerosis (pwMS), and impaired postural control is an important predictor of falls. Lab-based technology to measure posture is precise but expensive, and clinical tests may not capture underlying impairments. An alternative solution is to leverage smartphone accelerometry as it is affordable, ubiquitous, and portable.

RESEARCH QUESTION

Can smartphone accelerometry measure postural control compared to a force plate and research grade accelerometer in pwMS, and can smartphone accelerometry discriminate between assisted device and non-assisted device users?

METHODS

27 pwMS (12 assisted device users, 15 non-assisted device users) stood on a force plate while holding a smartphone with an attached research grade accelerometer against their chest. Participants performed two, 30 s trials of: eyes open, eyes closed, semi-tandem, tandem, and single leg. Acceleration and center of pressure were extracted, and Root Mean Square (RMS) and 95 % confidence ellipse were calculated. Spearman's correlations were performed, and receiving operating characteristic (ROC) curves and the Area Under the Curve (AUC) were calculated.

RESULTS

There were moderate to high correlations between the smartphone and accelerometer for RMS (ρ = 0.85 - 1.0; p = 0.001 - <0.001) and 95 % area ellipse (ρ = 0.92 - 0.99; p = <0.001). There were weak to moderate correlations between the smartphone and force plate for RMS (ρ = 0.38 - 0.92; p = 0.06 - <0.001) and 95 % area ellipse (ρ = 0.69 - 0.90 p = 0.002 - <0.001). To discriminate between assisted device usage, ROC curves for smartphone outputs were constructed, the AUC was high and statistically significant (p < 0.001 - 0.02).

SIGNIFICANCE

There is potential to leverage smartphone accelerometery to measure postural control in pwMS. These finding provide preliminary results to support the development of a mobile health application to measure fall risk for pwMS.

The Validity, Reliability, and Sensitivity of a Smartphone-Based Seated Postural Control Assessment in Wheelchair Users: A Pilot Study

Seated postural control is essential for wheelchair users to maintain proper position while performing activities of daily living. Clinical tests are commonly used to measure seated postural control, yet they are subjective and lack sensitivity. Lab-based measures are highly sensitive but are limited in scope and restricted to research settings. Establishing a valid, reliable, and accessible measurement tool of seated postural control is necessary for remote, objective assessments. Therefore, the purpose of this study was to examine the validity, reliability, and sensitivity of smartphone-based postural control assessments in wheelchair users. Eleven participants (age: 35.4 ± 17.9) completed two experimental visits 1-week apart consisting of three clinical tests: Trunk Control Test (TCT), Function in Sitting Test (FIST), and Tee-shirt Test, as well as, standardized instrumented balance tasks that manipulated vision (eyes open and closed), and trunk movement (functional reach and stability boundary). During these tasks, participants held a smartphone instrumented with a research-grade accelerometer to their chest. Maximum and root mean square (RMS) acceleration in the medial-lateral (ML) and anterior-posterior (AP) axes were derived. Participants were grouped into non-impaired and impaired postural groups based on FIST scores. Spearman rank-order correlations were conducted between the two devices' outcome measurements and between these measures and those of the clinical tests. Receiver operating characteristic (ROC) curves and the area under the curves (AUC) were determined to distinguish participants with and without impaired postural control. The reliability of outcome variables was assessed using inter-class correlations. Strong correlations between outputs derived from the smartphone and research-grade accelerometer were seen across balance tasks (ρ = −0.75–1.00; p ≤ 0.01). Numerous significant moderate correlations between clinical test outcomes and smartphone and research-grade RMS ML accelerometry were seen (ρ = −0.62 to 0.83 (p ≤ 0.044)]. On both devices, the AUC for ROC plots were significant for RMS ML sway during the eyes open task and functional stability boundary (p < 0.05). Reliability of smartphone accelerometry was comparable to the research-grade accelerometer and clinical tests. This pilot study illustrated that smartphone-based accelerometry may be able to provide a valid and reliable assessment of seated postural control and have the ability to distinguish between those with and without impaired postural control.

Feasibility and acceptability study on the use of a smartphone application to facilitate balance training in the ageing population

OBJECTIVES

This study aims to investigate the feasibility and acceptability of using an app-based technology to train balance in the older population.

DESIGN

Prospective feasibility study.

SETTING

The study was conducted in a university setting and participants' homes.

PARTICIPANTS

Thirty-five volunteers ≥55 years old were recruited.

INTERVENTION

Participants were asked to follow a balance exercise programme 7 days a week for 3 weeks using a phone application. Seventeen participants trained for a further 3 weeks.

OUTCOME MEASURES

Postural sway measures during quiet standing with feet at shoulder width apart and feet together, one leg standing and tandem stance were measured at baseline, and at the end of the 3 and 6 training weeks; the International Physical Activity Questionnaire (IPAQ) assessed participants' physical activity level before training; and app acceptability was recorded using a user experience questionnaire.

RESULTS

Participants on the 3 and 6-week programme on average completed 20 (±5) and 38 (±11) days of training, respectively, and all scored moderate to high on the IPAQ. Between baseline and the 3-week assessments, statistically significant improvements were observed for anteroposterior sway, mediolateral sway, sway area during tandem stance, for anteroposterior sway during one leg standing and for sway area during feet together stance. Improvements were observed at 6 week compared with baseline but those between 3 and 6 weeks were not significant. Based on the questionnaire, participants reported that the app is an appropriate tool for balance training (77%), they reported benefits from the training (50%) and found it easy to fit it into daily routine (88%).

CONCLUSION

The high level of adherence and improvements observed in the analysed measures demonstrate the feasibility of using an app to train balance in moderately to highly physically active older participants. This demonstrates that given appropriate tools the older population is positive towards and receptive of digital interventions aimed to improve balance.

Validity and reliability of smartphone use in assessing balance in patients with chronic ankle instability and healthy volunteers: A cross-sectional study

BACKGROUND

Chronic ankle instability (CAI) is associated with defective posture control and balance; thus, a proper assessment of these impairments is necessary for effective clinical decision-making. There is a need for portable, valid, and reliable methods to facilitate the easy collection of real-world data, such as mobile phones.

RESEARCH QUESTION

Is the smartphone "MyAnkle" application valid and reliable in assessing balance in patients with CAI and healthy volunteers?

METHODS

This was a cross-sectional study. Sixty-five participants completed two assessment sessions, including 31 patients (n = 41 ankles with CAI and 21 asymptomatic ankles) and 34 healthy volunteers (n = 68 ankles). In each session, dynamic single-leg stance balance was measured simultaneously using the "MyAnkle" application and the Biodex balance system (BBS) version 3. Testing was conducted at three levels of BBS difficulty-4 (D4, hard, loose platform), 6 (D6, moderate), and 8 (D8, easy, stiffer platform)-and repeated with opened and closed eyes. Both limbs were tested in a random order by two independent blinded assessors.

RESULTS

The two devices showed significant poor-to-moderate correlations when eyes were closed (p < 0.05). For discriminant validity, the application did not distinguish the two study groups in all tested conditions (p > 0.05), whereas the BBS weakly to moderately distinguished the dominant limbs in the two groups at all difficulty levels with eyes-open and at D8 with eyes-closed regardless to limb dominance. For reliability, a significantly poor to moderate inter-session reliability was noted for the two devices.

SIGNIFICANCE

"MyAnkle" application is valid in assessing balance in patients with CAI when the eyes are closed. However, similarly to BBS, its one-week test-retest reliability may be insufficient for accurate follow-up of balance changes and need to be interpreted with caution. Future studies need to establish its inter-tester reliability and its usefulness in telerehabilitation.

Enabling Older Adults' Health Self-Management through Self-Report and Visualization-A Systematic Literature Review

Aging is associated with a progressive decline in health, resulting in increased medical care and costs. Mobile technology may facilitate health self-management, thus increasing the quality of care and reducing costs. Although the development of technology offers opportunities in monitoring the health of older adults, it is not clear whether these technologies allow older adults to manage their health data themselves. This paper presents a review of the literature on mobile health technologies for older adults, focusing on whether these technologies enable the visualization of monitored data and the self-reporting of additional information by the older adults. The systematic search considered studies published between 2009 and 2019 in five online databases. We screened 609 articles and identified 95 that met our inclusion and exclusion criteria. Smartphones and tablets are the most frequently reported technology for older adults to enter additional data to the one that is monitored automatically. The recorded information is displayed on the monitoring device and screens of external devices such as computers. Future designs of mobile health technology should allow older users to enter additional information and visualize data; this could enable them to understand their own data as well as improve their experience with technology.

Development of a mobile application to screen and manage fall risks in older people

Objective: Falls and related injuries are known to be the major health problem leading to disability and mortality among older adults. Identification and management of fall risks aimed to prevent falling is considered to be essential. The aim of this study was to develop a mobile application for screening and management of fall risks based for older adults.Method and materials: First, we determined product features based on literature reviews. Then we asked 10 experts to assess the importance of capabilities. The application was designed in Android environment based on the STEADI toolkit. Finally, the usability and satisfaction of the application were assessed among 30 older adults by means of a usability questionnaire, and the final version was modified.Results: The experts rated the majority of feasibility features to be important. The application consisted of falls risk self-assessment, and the Timed Up and Go (TUG) test to measure individual fall risks, fall prevention education, and suggestions for training based on the individuals' level of fall risk among older adults. The results of the usability assessment showed that the users were satisfied with the application, 8.83 out of 10.Conclusion: The mobile application can be used to screen and manage fall risks in older adults. It may help health providers to identify older adults at low, moderate, and high risks of falls provide education and training to minimise falls and fall-related injuries.Implications for rehabilitationFalls are a major health problem in older people. A great proportion of falls and falls related injuries are preventable.Given the availability and accessibility of various mobile health application and the increasing mobile device usage among older adults, mobile application can be used as a platform for delivering fall prevention programmes such as education and exercise training.The mobile application may be a valuable tool in the fall prevention and their consequences either in old adult.

Co-Creation with Older Adults to Improve User-Experience of a Smartphone Self-Test Application to Assess Balance Function

This co-creation study aimed to develop a smartphone self-test application for balance and leg strength in collaboration between older adults and the research team. The paper describes older participants’ preferences for, and their contribution to, the application design. Technology to assess movements is available in smartphones with built-in sensors, and one of the challenges is to develop a valuable self-test for older adults. The participants contributed to the design of the application’s instructions and user interface. Multiple data collection methods were used: user-test with Think aloud method, mock-ups, homework assignment as co-researcher, audio and video recordings. Qualitative content analysis with a deductive-inductive approach was used, guided by the Optimized Honeycomb model for user experience (UX) as a categorization matrix. The analysis resulted in 17 subcategories within the seven facets of the UX Honeycomb model (findable, accessible, usable, desirable, credible, useful, and valuable), and describes the older participants’ preferences and experiences. The main results were participants’ desire to know why, to get clear and appropriate information, and expectations of the self-test to be useful. It was feasible and valuable to develop the self-test application in co-creation with the intended user-group, in order to get direct feedback and suggestions for the development.

Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance

The assessment of trunk sway smoothness using an accelerometer sensor embedded in a smartphone could be a biomarker for tracking motor learning. This study aimed to determine the reliability of trunk sway smoothness and the effect of visual biofeedback of sway smoothness on motor learning in healthy people during unipedal stance training using an iPhone 5 measurement system. In the first experiment, trunk sway smoothness in the reliability group (n = 11) was assessed on two days, separated by one week. In the second, the biofeedback group (n = 12) and no-biofeedback group (n = 12) were compared during 7 days of unipedal stance test training and one more day of retention (without biofeedback). The intraclass correlation coefficient score 0.98 (0.93–0.99) showed that this method has excellent test–retest reliability. Based on the power law of practice, the biofeedback group showed greater improvement during training days (p = 0.003). Two-way mixed analysis of variance indicates a significant difference between groups (p < 0.001) and between days (p < 0.001), as well as significant interaction (p < 0.001). Post hoc analysis shows better performance in the biofeedback group from training days 2 and 7, as well as on the retention day (p < 0.001). Motor learning objectification through visual biofeedback of trunk sway smoothness enhances postural control learning and is useful and reliable for assessing motor learning.

Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review

Wearable sensors are de facto revolutionizing the assessment of standing balance. The aim of this work is to review the state-of-the-art literature that adopts this new posturographic paradigm, i.e., to analyse human postural sway through inertial sensors directly worn on the subject body. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 73 full-text articles, selecting 47 high-quality contributions. A good inter-rater reliability was obtained (Cohen's kappa = 0.79). This selection of papers was used to summarize the available knowledge on the types of sensors used and their positioning, the data acquisition protocols and the main applications in this field (e.g., "active aging", biofeedback-based rehabilitation for fall prevention, and the management of Parkinson's disease and other balance-related pathologies), as well as the most adopted outcome measures. A critical discussion on the validation of wearable systems against gold standards is also presented.

Can We Rely on Mobile Devices and Other Gadgets to Assess the Postural Balance of Healthy Individuals? A Systematic Review

The consequences of falls, costs, and complexity of conventional evaluation protocols have motivated researchers to develop more effective balance assessments tools. Healthcare practitioners are incorporating the use of mobile phones and other gadgets (smartphones and tablets) to enhance accessibility in balance evaluations with reasonable sensitivity and good cost–benefit. The prospects are evident, as well as the need to identify weakness and highlight the strengths of the different approaches. In order to verify if mobile devices and other gadgets are able to assess balance, four electronic databases were searched from their inception to February 2019. Studies reporting the use of inertial sensors on mobile and other gadgets to assess balance in healthy adults, compared to other evaluation methods were included. The quality of the nine studies selected was assessed and the current protocols often used were summarized. Most studies did not provide enough information about their assessment protocols, limiting the reproducibility and the reliability of the results. Data gathered from the studies did not allow us to conclude if mobile devices and other gadgets have discriminatory power (accuracy) to assess postural balance. Although the approach is promising, the overall quality of the available studies is low to moderate.

Balance and Gait Alterations Observed More Than 2 Weeks After Concussion: A Systematic Review and Meta-Analysis

OBJECTIVE

The aim of the study was to systematically review and quantitatively synthesize the existing evidence of balance and gait alterations lasting more than 2 wks after concussion in adults.

DESIGN

A systematic review was conducted through PubMed, CINAHL, SPORTDiscus, and Web of Science. Investigations must include adult participants with at least one concussion, were measured for 14 days after injury, and reported balance or gait measures. Balance error scoring system scores, center of pressure sway area and displacement, and gait velocity were extracted for the meta-analysis.

RESULTS

Twenty-two studies were included. Balance alterations were observed for 2 wks after concussion when participants were tested with eyes closed, for longer durations of time, and with nonlinear regulatory statistics. The meta-analysis of center of pressure sway area with no visual feedback indicated that concussed individuals had greater sway area (P < 0.001). Various gait alterations were also observed, which may indicate that concussed individuals adopt a conservative gait strategy. The meta-analysis revealed that concussed participants walked 0.12 m/sec (P < 0.001) and 0.06 m/sec (P = 0.023) slower in single and dual-task conditions, respectively.

CONCLUSIONS

Subtle balance and gait alterations were observed after 2 wks after a concussion. Understanding these alterations may allow clinicians to improve concussion diagnosis and prevent subsequent injury.

Preliminary evaluation of a self-guided fall risk assessment tool for older adults

Falls are a major health problem for older adults with significant physical and psychological consequences. The first step of successful fall prevention is to identify those at risk of falling. Recent technology advancement offers the possibility of objective, lowcost and self-guided fall risk assessment. The present work evaluated the preliminary validity and usability of a Kinect camera-based selfinitiated fall risk assessment system in a hospital setting. A convenience sample of 29 female participants (77.5 ± 7.9 years old) enrolled in this study. This low-cost self-guided system included a Kinect depth-sensing camera, a PC-based computer, and custom-built software. An onscreen Fall Risk Assessment Avatar (FRAAn) utilizing visual and verbal instructions led participants through a fall risk assessment consisting of self-report measures and clinically validated balance and mobility tests. Participants also completed clinical fall risk evaluation (Timed-Up and Go, and Berg Balance Scale) led by a researcher. User experience was evaluated by the System Usability Scale (SUS). Results indicate that FRAAn-based outcome measures (postural sway metrics, and sit-to-stand speed) were highly correlated with clinical fall risk measures, and were able to differentiate individuals with increased fall risk. Additionally, 83% participants reported high usability (SUS > 80), indicating the system is well received among older users. Overall, our results indicate that the FRAAn system has promise for providing a self-guided fall risk assessment, and is well received by older users. This affordable, portable and self-guided system has potential to facilitate objective fall risk assessment in older adults in various settings.

Smartphone technology can measure postural stability and discriminate fall risk in older adults

BACKGROUND

Falls are the leading cause of injury related death in older adults. Impaired postural stability is a predictor of falls but is seldom objectively assessed in clinical or home settings. Embedded accelerometers within smartphones offer potential to objectively measure postural stability. The purpose of this study was to determine if a smartphone embedded accelerometer can measure static postural stability and distinguish older adults at high levels of fall risk.

METHODS

Thirty older adults (age: 65.9 ± 8.8) underwent seven balance tests while standing on a force plate and holding a smartphone against their chest in a standardized order. Participants also completed the Physiological Profile Assessment to assess their fall risk. Center of pressure (COP) parameters from the force plate including velocity in the anterioposterior (AP) and mediolateral (ML) directions and 95% confidence ellipse were derived. Maximum acceleration and root mean square (RMS) in ML, AP and vertical axes were derived from the smartphone. Spearman rank-order correlations between force plate and smartphone measures were conducted, and receiver operating characteristic (ROC) and the area under the curves (AUC) were constructed to distinguish between low and high fall risk.

RESULTS

There were moderate to strong significant correlations between measures derived from the force plate and measures derived from the smartphone during challenging balance conditions (ρ = 0.42-0.81; p < 0.01-0.05). The AUC for ROC plots were significant for all COP measures during challenging balance conditions (p < 0.01-0.05). The AUC for ROC plots were significant for RMS vertical and AP during challenging balance conditions (p = 0.01-0.04).

SIGNIFICANCE

This study provides evidence that a smartphone is a valid measure of postural stability and capable of distinguishing fall risk stratification in older adults. There is potential for smartphones to offer objective, fall risk assessments for older adults.

Physical performance and cognitive functioning among individuals with diabetes: Findings from the China Health and Retirement Longitudinal Study Baseline Survey

AIMS

The purpose of this study was to examine individual associations of each physical performance measure with domains of cognitive functioning and to determine best physical performance measures strongly associated with each domain of cognitive functioning among middle-aged and older adults with diabetes.

BACKGROUND

Tests of physical performance are strongly correlated with cognitive decline in general elderly population. However, far less is known about individual associations of each individual physical performance measure with domains of cognitive functioning among individuals with diabetes.

DESIGN

The study employed a retrospective, cross-sectional design.

METHODS

Baseline data from a national baseline survey collected from May 2011-March 2012 were used. A total of 17,314 individuals aged ≥45 years completed the baseline survey. Diabetes was confirmed for 1,905 participants and these individuals were included in this study.

RESULTS

When grip strength, walking speed, repeated chair stands and standing balance test were added in the regression models, walking speed was the only variable that was significantly associated with figure drawing and grip strength was the only variable that was significantly associated with episodic memory, orientation/attention and overall cognitive score.

CONCLUSION

Since grip strength was the most important factor associated with several domains of cognitive functioning, strategies that improve grip strength in patients with diabetes are prudent. Early interventions to increase levels of physical activity may be important to improve both grip strength and cognitive functioning in this growing population with diabetes.

A Fall Risk mHealth App for Older Adults: Development and Usability Study

BACKGROUND

Falls are the leading cause of injury-related death in older adults. Due to various constraints, objective fall risk screening is seldom performed in clinical settings. Smartphones offer a high potential to provide fall risk screening for older adults in home settings. However, there is limited understanding of whether smartphone technology for falls screening is usable by older adults who present age-related changes in perceptual, cognitive, and motor capabilities.

OBJECTIVE

The aims of this study were to develop a fall risk mobile health (mHealth) app and to determine the usability of the fall risk app in healthy, older adults.

METHODS

A fall risk app was developed that consists of a health history questionnaire and 5 progressively challenging mobility tasks to measure individual fall risk. An iterative design-evaluation process of semistructured interviews was performed to determine the usability of the app on a smartphone and tablet. Participants also completed a Systematic Usability Scale (SUS). In the first round of interviews, 6 older adults participated, and in the second round, 5 older adults participated. Interviews were videotaped and transcribed, and the data were coded to create themes. Average SUS scores were calculated for the smartphone and tablet.

RESULTS

There were 2 themes identified from the first round of interviews, related to perceived ease of use and perceived usefulness. While instructions for the balance tasks were difficult to understand, participants found it beneficial to learn about their risk for falls, found the app easy to follow, and reported confidence in using the app on their own. Modifications were made to the app, and following the second round of interviews, participants reported high ease of use and usefulness in learning about their risk of falling. Few differences were reported between using a smartphone or tablet. Average SUS scores ranged from 79 to 84.

CONCLUSIONS

Our fall risk app was found to be highly usable by older adults as reported from interviews and high scores on the SUS. When designing a mHealth app for older adults, developers should include clear and simple instructions and preventative strategies to improve health. Furthermore, if the design accommodates for age-related sensory changes, smartphones can be as effective as tablets. A mobile app to assess fall risk has the potential to be used in home settings by older adults.

Novel technology for mobility and balance tracking in patients with multiple sclerosis: a systematic review

INTRODUCTION

Mobility and balance impairments in patients with multiple sclerosis (MS) are major factors for decreased quality of life. Novel sensing technologies have great potential to efficiently capture subtle changes in mobility and balance performance, and thus improve current practices by providing an easy-to-implement, objective, and continuous functional tracking in MS population. Areas covered: This review details the collective findings of novel technology utilization in mobility and balance tracking in patients with MS. Thirty-three were systematically identified and included in this review. Pertinent methodological features (participant demographics, sensing technology, study aims, functional assessment protocols, and outcome measures) were extracted from each article. The construct validity, reliability, clinical relevance, and discriminative ability of sensor-based assessment in the MS population were summarized. Expert commentary: Sensor-based balance and mobility assessment are valid in comparison with reference standard techniques and are reliable to measure performance in the MS population. Sensor-based measures are also associated with validated clinical outcomes and are sensitive to functional deficits in individuals with MS. Such technologies may greatly improve the likelihood of detecting mobility and balance dysfunctions in real-world environments, thus allowing healthcare professionals to monitor interventions and manage disease progression precisely and efficiently Abbreviations: PwMS: Patients with Multiple Sclerosis; BBS: Berg Balance Scale; DGI: Dynamic Gait Index; ABC: Activity-specific Balance Confidence; T25FW: Timed 25 Foot Walk; 6MWT: 6 minute walk test; TUG: Timed Up and Go test; EO: Eyes Open; EC: Eyes Closed; ICC: Intraclass Correlation Coefficient; EDSS: Expanded Disability Status Scale; MFIS: Modified Fatigue Impact Scale; MSWS: Multiple Sclerosis Walking Scale; MSIS: Mutliple Sclerosis Impact Scale; PPA: Physiological Profile Assessment; HC: Healthy Control; AP: Anterior-posterior direction; ML: Mediolateral direction.

Smartphone Applications to Perform Body Balance Assessment: a Standardized Review

Body balance disorders are related to different injuries that contribute to a wide range of healthcare issues. The social and financial costs of these conditions are high. Therefore, quick and reliable body balance assessment can contribute to the prevention of injuries, as well as enhancement of clinical rehabilitation. Moreover, the use of smartphone applications is increasing rapidly since they incorporate different hardware components that allow for body balance assessment. The present study aims to show an analysis of the current applications available on Google Play Store^TM and iTunes App Store^TM to measure this physical condition, using the Mobile Application Rating Scale (MARS). Three iOS and two Android applications met the inclusion criteria. Three applications have scientific support, Balance test YMED, Balance Test by Slani, and Sway. Furthermore, according to MARS, the main scores for each evaluated domain were: Engagement (2.04), Functionality (3.8), Esthetics (3.53), and Information (3.80). The reviewed applications targeted to assess body balance obtained good mean scores. Sway is the app with highest scores in each MARS domain, followed by iBalance Fitness and Gyrobalance.