Smartphone Applications to Perform Body Balance Assessment: a Standardized Review

mHealth Impact on Gait and Dynamic Balance Outcomes in Neurorehabilitation: Systematic Review and Meta-analysis

Gait and dynamic balance are two main goals in neurorehabilitation that mHealth systems could address. To analyze the impact of using mHealth systems on gait and dynamic balance outcomes in subjects with neurological disorders. Randomized controlled trials (RCT) published in PubMed, Web of Science, Scopus, and PEDro databases were searched up to April 2023. Studies including adults with neurological disorders, analyzing the effectiveness of mHealth systems on gait and dynamic balance compared with conventional therapy and/or not intervention, were included. The PEDro scale and the Cochrane Collaboration's 2.0 tool were used for the methodological quality and risk of bias assessment. The Review Manager 5.4 software was used to obtain meta-analyses. 13 RCT were included in the systematic review and 11 in the meta-analyses, involving 528 subjects. A total of 21 mobile applications were identified for gait and balance training, and to enhance physical activity behaviors. There were significant differences in gait parameters, speed by 0.10 s/m (95% confidence interval (CI)=0.07,0.13;p<0.001), cadence by 8.01 steps/min (95%CI=3.30,12.72;p<0.001), affected step length by 8.89 cm (95%CI=4.88,12.90;p<0.001), non-affected step length by 8.08 cm (5%CI=2.64,13.51;p=0.004), and in dynamic balance, Timed Up and Go by -7.15 s (95%CI=-9.30,-4.99;p<0.001), and mobility subscale of Posture Assessment Scale for Stroke by 1.71 points (95%CI=1.38,2.04;p<0.001). Our findings suggested the use of mHealth systems for improving gait in subjects with neurological disorders, but controversial results on dynamics balance recovery were obtained. However, the quality of evidence is insufficient to strongly recommend them, so further research is needed.

Smartphone Technology to Remotely Measure Postural Sway during Double- and Single-Leg Squats in Adults with Femoroacetabular Impingement and Those with No Hip Pain

BACKGROUND

The COVID-19 pandemic has accelerated the demand for utilising telehealth as a major mode of healthcare delivery, with increasing interest in the use of tele-platforms for remote patient assessment. In this context, the use of smartphone technology to measure squat performance in people with and without femoroacetabular impingement (FAI) syndrome has not been reported yet. We developed a novel smartphone application, the TelePhysio app, which allows the clinician to remotely connect to the patient's device and measure their squat performance in real time using the smartphone inertial sensors. The aim of this study was to investigate the association and test-retest reliability of the TelePhysio app in measuring postural sway performance during a double-leg (DLS) and single-leg (SLS) squat task. In addition, the study investigated the ability of TelePhysio to detect differences in DLS and SLS performance between people with FAI and without hip pain.

METHODS

A total of 30 healthy (nfemales = 12) young adults and 10 adults (nfemales = 2) with diagnosed FAI syndrome participated in the study. Healthy participants performed DLS and SLS on force plates in our laboratory, and remotely in their homes using the TelePhysio smartphone application. Sway measurements were compared using the centre of pressure (CoP) and smartphone inertial sensor data. A total of 10 participants with FAI (nfemales = 2) performed the squat assessments remotely. Four sway measurements in each axis (x, y, and z) were computed from the TelePhysio inertial sensors: (1) average acceleration magnitude from the mean (aam), (2) root-mean-square acceleration (rms), (3) range acceleration (r), and (4) approximate entropy (apen), with lower values indicating that the movement is more regular, repetitive, and predictable. Differences in TelePhysio squat sway data were compared between DLS and SLS, and between healthy and FAI adults, using analysis of variance with significance set at 0.05.

RESULTS

The TelePhysio aam measurements on the x- and y-axes had significant large correlations with the CoP measurements (r = 0.56 and r = 0.71, respectively). The TelePhysio aam measurements demonstrated moderate to substantial between-session reliability values of 0.73 (95% CI 0.62-0.81), 0.85 (95% CI 0.79-0.91), and 0.73 (95% CI 0.62-0.82) for aamx, aamy, and aamz, respectively. The DLS of the FAI participants showed significantly lower aam and apen values in the medio-lateral direction compared to the healthy DLS, healthy SLS, and FAI SLS groups (aam = 0.13, 0.19, 0.29, and 0.29, respectively; and apen = 0.33, 0.45, 0.52, and 0.48, respectively). In the anterior-posterior direction, healthy DLS showed significantly greater aam values compared to the healthy SLS, FAI DLS, and FAI SLS groups (1.26, 0.61, 0.68, and 0.35, respectively).

CONCLUSIONS

The TelePhysio app is a valid and reliable method of measuring postural control during DLS and SLS tasks. The application is capable of distinguishing performance levels between DLS and SLS tasks, and between healthy and FAI young adults. The DLS task is sufficient to distinguish the level of performance between healthy and FAI adults. This study validates the use of smartphone technology as a tele-assessment clinical tool for remote squat assessment.

Evaluating and rating HIV/AIDS mobile apps using the feature-based application rating method and mobile app rating scale

Background

The purpose of this study was to evaluate HIV/AIDS mobile applications using the Mobile App Rating Scale (MARS) and rate the features of these applications using the new tool called the Feature-based Application Rating Method (FARM).

Methods

In this study, all available HIV/AIDS apps in Iran from Cafe Bazaar and Google Play Store due to inclusion criteria were studied. The evaluation of the quality of applications was done using the MARS tool and the FARM tool. The FARM, which was developed in this study, was applied to rank the features of the applications.

Results

In this study, 79 applications were included. The mean score of all apps using both tools was 3.58 (SD = 0.95) out of 5. The overall mean quality score based on the MARS was 3.14 (SD = 0.84), and the mean score of features based on FARM was 3.81 (SD = 1.23). This study showed a higher than moderate correlation between the scores assigned to apps based on the MARS and FARM tools (r > 0.4).

Conclusions

The HIV/AIDS mobile applications available in Iran had the "acceptable" ranking. Also, our study results showed that to evaluate mobile apps, using a single tool may not provide good insight to evaluators about the assessed apps. However, using more than one tool may provide more details about the evaluated apps. To improve the quality of mobile health apps and help users select the most desirable app, we suggested using tools like FARM for ranking apps based on the features of each app in the app stores.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-02029-8.

Use of Filters to Smooth Out Signals Collected through Mobile Devices in the Static and Dynamic Balance Assessment: A Systematic Review

Background: When performing motion analysis using sensors, the signal often comes with noise and it is necessary to use filters to exclude unwanted frequencies. For this reason, the objective of this work was to carry out a systematic review on the filters used in data recorded from smartphone applications for static and dynamic balance assessment. Methods: A systematic literature review was performed on the PubMed, ScienceDirect, Scopus, Technology Research and Web of Science databases, using the search strategy: smartphone, “mobile technology”, evaluation, “postural stability”, and balance. Results: 427 articles were found (PubMed = 107; ScienceDirect = 67; Scopus = 106; Web of Science = 95; Technology research database = 52). After applying the inclusion criteria and removing duplicates, nine studies were eligible for this review. In these studies, the fourth-order Butterworth low-pass filter was the most applied (N = 6) and the cutoff frequency of 4 Hz (N = 2) was the most frequent. Conclusions: In general, few studies have adequately described the filter used in signal processing. This step, when hidden, negatively affects the reproducibility of studies. Understanding and describing the signal processing is important not only for the correct description of the results but also for the reproducibility of the studies.

Static Balance Digital Endpoints with Mon4t: Smartphone Sensors vs. Force Plate

Static balance tests are conducted in various clinics for diagnosis and treatment adjustment. As a result of population aging, the accessibility of these tests should be increased, in the clinic, and for remote patient examination. A number of publications have already conducted static balance evaluations using the sensors embedded in a smartphone. This study focuses on the applicability of using smartphone-based balance assessment on a large scale while considering ease of use, safety, and reliability. The Mon4t^® app was used to acquire the postural motion using different smartphone devices, different smartphone locations, and various standing postures. The signals derived from the app were compared to the center of pressure displacement derived from a force plate. The results showed moderate to high agreement between the two methods, particularly at the tandem stance (0.69 ≤ r ≤ 0.91). Preliminary data collection was conducted on three healthy participants, followed by 50 additional healthy volunteers, aged 65+. The results demonstrated that the Mon4t app can serve as an accessible and inexpensive static balance assessment tool, both in clinical settings and for remote patient monitoring, which is key for enabling telehealth.

Validity and reliability of balance Y-MED application in chronic mechanical low back pain patients

Background

Low back pain patients suffer from balance disturbance. Balance allows a person to interact with the surrounding environment and to do his daily activities. As recent technology has facilitated patient monitoring and enhanced our ability to monitor patients remotely, smartphone apps have been developed to achieve this goal. There are various balance assessment instruments used nowadays. It may be subjective or objective assessments. This study was applied to verify if the measurements of balance Y-MED smartphone applications are valid and reliable compared to the HUMAC balance board in order to offer easy, fast, cost-effective, and time-effective valid and reliable balance assessment that can be used in a clinical setting.

Methods

Fifty-four patients (12 males and 42 females) with chronic mechanical low back pain for more than 3 months was volunteered to participate in the current study with an age range of 25–60 years and BMI range of 18–34 kg/m2. Compared with the HUMAC balance board, the validity of the balance Y-MED smartphone application is evaluated, and the test-retest reliability of the balance Y-MED smartphone application is obtained by the same examiner 3 times.

Results

For concurrent validity, the correlations between balance measurements by Y-MED smartphone application and HUMAC balance board were not significant in both eyes open (r = − 0.12, p = 0.38) and eyes closed (r = 0.26, p = 0.054). The smartphone application showed poor test-retest reliability measurement of balance with eyes open; (ICC was 0.279, with 95% CI − 0.117–0.554) and with eyes closed (ICC was − 0.159, with 95% CI − 0.814–0.287).

Conclusions

According to the evaluation scheme selected in this study, the researchers were unable to confirm the validity of the balance Y-MED smartphone application in the balance assessment of patients with mechanical chronic low back pain. More than that, the balance Y-MED smartphone application has been shown poor score reliability. This makes it inaccurate for use in assessment balance.

Balance Differences between North and South American Older Adults: A Cross-Sectional, Age and Sex Matched Study

This study aimed to characterize the risk of falling in low-, moderate- and high-risk participants from two different geographical locations using a portable force-plate. A sample of 390 older adults from South and North America were matched for age, sex, height and weight. All participants performed a standardized balance assessment using a force plate. Participants were classified in low, moderate and high risk of falling. No differences were observed between South and North American men, nor comparing North American men and women. South American women showed the significantly shorter center of pressure path length compared to other groups. The majority of the sample was categorized as having low risk of falling (male: 65.69% and female: 61.87%), with no differences between men and women. Moreover, no differences were found between North vs. South Americans, nor between male and female groups compared separately. In conclusion, South American women had better balance compatible with the status of the 50–59 years’ normative age-range. The prevalence of low falls risk was~61–65%; the prevalence of moderate to high risk was~16–19%. The frequency of fall risk did not differ significantly between North and South Americans, nor between males and females.

Status of the research in fitness apps: A bibliometric analysis

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A bibliometric analysis of the fitness apps research field to gain insight into the state of the art.

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Scopus and Web of Science were used to collect the data (481 records).

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Statistical analysis and science mapping were used to analyze the data.

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Provides basic data, research classifications and future research directions in the area.

Fitness applications have undergone considerable development in the last few years and becoming popular and significant in both academic and practical areas. However, contributions to the systematic mapping of this field continue to be lacking. This paper constitutes the first bibliometric study in this field to better understand the current state of research. We examined 481 records from databases Scopus and Web of Science (Core Collection) using several bibliometric analysis methods. All the records on this emerging topic were published between 2011 and 2019. We processed these records using statistical analysis and science mapping. The bibliometric analysis included the year of publication, journal name, citation, author, country, and particularly, research methodology. Additionally, we used the VOSViewer software to perform bibliometric mapping of co-authorship, co-citation of authors, and co-occurrence of keywords. This field of study, it was found, is currently in its precursor stage, contributing primarily to the fields of medicine, computer science, and health sciences. The United States appeared to have made the largest contribution to this field. However, author productivity, number of citations, and number of core journals all indicated a high degree of fragmentation of research in this filed. Remarkably, scientific research in this area is expected to progress tremendously over time. Overall, this study provides basic data and research classifications for the initial phase of research and research direction for future research in this area.

Analysis of Apps With a Medication List Functionality for Older Adults With Heart Failure Using the Mobile App Rating Scale and the IMS Institute for Healthcare Informatics Functionality Score: Evaluation Study

Background

Managing the care of older adults with heart failure (HF) largely centers on medication management. Because of frequent medication or dosing changes, an app that supports these older adults in keeping an up-to-date list of medications could be advantageous. During the COVID-19 pandemic, HF outpatient consultations are taking place virtually or by telephone. An app with the capability to share a patient’s medication list with health care professionals before consultation could support clinical efficiency, for example, by reducing consultation time. However, the influence of apps on maintaining an up-to-date medication history for older adults with HF in Ireland remains largely unexplored.

Objective

The aims of this review are twofold: to review apps with a medication list functionality and to assess the quality of the apps included in the review using the Mobile App Rating Scale (MARS) and the IMS Institute for Healthcare Informatics functionality scale.

Methods

A systematic search of apps was conducted in June 2019 using the Google Play Store and iTunes App Store. The MARS was used independently by 4 researchers to assess the quality of the apps using an Android phone and an iPad. Apps were also evaluated using the IMS Institute for Healthcare Informatics functionality score.

Results

Google Play and iTunes App store searches identified 483 potential apps (292 from Google Play and 191 from iTunes App stores). A total of 6 apps (3 across both stores) met the inclusion criteria. Of the 6 apps, 4 achieved an acceptable MARS score (3/5). The Medisafe app had the highest overall MARS score (4/5), and the Medication List & Medical Records app had the lowest overall score (2.5/5). On average, the apps had 8 functions based on the IMS functionality criteria (range 5-11). A total of 2 apps achieved the maximum score for number of features (11 features) according to the IMS Institute for Healthcare Informatics functionality score, and 2 scored the lowest (5 features). Peer-reviewed publications were identified for 3 of the apps.

Conclusions

The quality of current apps with medication list functionality varies according to their technical aspects. Most of the apps reviewed have an acceptable MARS objective quality (ie, the overall quality of an app). However, subjective quality (ie, satisfaction with the apps) was poor. Only 3 apps are based on scientific evidence and have been tested previously. A total of 2 apps featured all the IMS Institute for Healthcare Informatics functionalities, and half did not provide clear instructions on how to enter medication data, did not display vital parameter data in an easy-to-understand format, and did not guide users on how or when to take their medication.

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.

Validity and Reliability of Mobile Applications for Assessing Strength, Power, Velocity, and Change-of-Direction: A Systematic Review

This systematic review aimed to (1) identify and summarize studies that have examined the validity of apps for measuring human strength, power, velocity, and change-of-direction, and (2) identify and summarize studies that have examined the reliability of apps for measuring human strength, power, velocity, and change-of-direction. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 435 studies initially identified, 23 were fully reviewed, and their outcome measures were extracted and analyzed. In total, 11 mobile applications were analyzed and summarized for their validity and reliability to test movement velocity, movement time, movement displacement, power output, and workload. The present systematic review revealed that the tested apps are valid and reliable for measuring bar movement velocity during lower and upper body resistance exercises; however, systematic bias was detected with heavier loads.

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.

EDDAMAP: efficient data-dependent approach for monitoring asymptomatic patient

Background

A pandemic affects healthcare delivery and consequently leads to socioeconomic complications. During a pandemic, a community where there lives an asymptomatic patient (AP) becomes a potential endemic zone. Assuming we want to monitor the travel and/or activity of an AP in a community where there is a pandemic. Presently, most monitoring algorithms are relatively less efficient to find a suitable solution as they overlook the continuous mobility instances and activities of the AP over time. Conversely, this paper proposes an EDDAMAP as a compelling data-dependent technique and/or algorithm towards efficient continuous monitoring of the travel and/or activity of an AP.

Methods

In this paper, it is assumed that an AP is infected with a contagious disease in which the EDDAMAP technique exploits a GPS-enabled mobile device by tagging it to the AP along with its travel within a community. The technique further examines the Spatio-temporal trajectory of the AP to infer its spatial time-bounded activity. The technique aims to learn the travels of the AP and correlates them to its activities to derive some classes of point of interests (POIs) in a location. Further, the technique explores the natural occurring POIs via modelling to identify some regular stay places (SP) and present them as endemic zones. The technique adopts concurrent object feature localization and recognition, branch and bound formalism and graph theory to cater for the worst error-guaranteed approximation to obtain a valid and efficient query solution and also experiments with a real-world GeoLife dataset to confirm its performance.

Results

The EDDAMAP technique proofs a compelling technique towards efficient monitoring of an AP in case of a pandemic.

Conclusions

The EDDAMAP technique will promote the discovery of endemic zones and hence some public healthcare facilities can rely on it to facilitate the design of patient monitoring system applications to curtail a global pandemic.

Mobile Applications (Apps) to Support the Hepatitis C Treatment: A Systematic Search in App Stores

The purpose of this review was to identify apps to support the HCV treatment and perform a quality assessment. A comprehensive search was conducted until February 2020 in Apple App Store (iOs) and Google Play Store (Android) using search term such "hepatitis", "hepatology", and "HCV". Two independent authors identified the apps and performed data extraction and quality assessment using Mobile App Rating Scale (MARS). Spearman's correlation analysis was used to analyze the relationships between user's star ratings found in the app stores and quality app defined by the MARS instrument. A total of 316 potential apps were identified, of which 12 apps fully met the eligibility criteria. Most apps were available in both App Stores and developed by commercial developers for healthcare provider. Almost all of apps were updated within the last two year and received 3.7 or above star ratings from users. Overall, only one app was considered with a good quality. The average scores for objective and subjective MARS quality of these apps were 3.54 (SD = 0.65) and 3.27 (SD = 0.76), respectively. Moreover, a majority of apps received objective scores between 3.29 and 4.37/5. However, MARS items such "interactivity", "visual appeal", "quality information", and "credibility" obtained minimum acceptable scores. MARS scores were not significantly correlation the user's star ratings. This systematic search found gaps in apps to support the HCV treatment; 12 apps were identified in this study and only one app achieved a good quality. There is a need that users use these apps cautiously as well as involve expert healthcare professionals in the development of new HCV apps.

Sensorimotor training for injury prevention in collegiate soccer players: An experimental study

OBJECTIVES

Deliver a sensorimotor training intervention; quantify the change in clinical measurements of sensorimotor control; and compare injury rate to a historical control.

DESIGN

One-arm experimental pilot; Level 3.

SETTING

NCAA Division II university athletic facilities.

PARTICIPANTS

75 collegiate soccer players (38 males; 37 females) were enrolled, including 30 (40%) with history of concussion, and participated in eight training sessions.

OUTCOMES

Change in pre-to post-intervention for: static balance on the Sway app, near-point convergence, self-reported symptoms on the Post-Concussion Symptom Scale, cervical flexor neuromotor control/endurance, measured by the Cranial-Cervical Flexion Test and Joint Position Error test, and gaze stability on the Dynamic Visual Acuity Test. Injury incidence rate in 2018 was calculated using the number of traumatic injuries across the season and athlete exposure counts, as compared to a historical control.

RESULTS

Significant improvements were obtained in static balance, cervical flexor neuromotor control/endurance, and near-point convergence (p-values<0.01-0.03). Increases in symptom report (p = 0.02) and a decline in dynamic gaze stability (p < 0.01) were observed. There were 11.8 injuries/1000 athlete exposures in 2017 and 8.9 injuries/1000 athlete exposures in 2018 after the treatment (p = 0.18).

CONCLUSION

This intervention holds promise as a preventive strategy for sports-injury as a comprehensive population-based intervention.

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.