Dataset Information

Performing Dynamic Weight-Shifting Balance Exercises With a Smartphone-Based Wearable Telerehabilitation System for Home Use by Individuals With Parkinson's Disease: A Proof-of-Concept Study.

ABSTRACT: Telerehabilitation technology often helps individuals with Parkinson's disease (PD) to control their balance and improve postural stability. This proof-of-concept study describes the redesign of a smartphone-based wearable balance rehabilitation system, or Smarter Balance System (SBS) intended for in-home use, and determines the number of exercise sessions required to achieve steady-state balance exercise performance by people with PD who performed 6 weeks of in-home dynamic weight-shifting balance exercises. The redesigned SBS supplied real-time multimodal (visual and vibrotactile) biofeedback during dynamic weight-shifting balance exercises (WSBEs). A Technology Acceptance Model (TAM) questionnaire completed by participants validated its acceptability and use. The results of regression analyses of participants' balance exercise performance, based on the average cross-correlations and absolute position errors between the target motion and the exerciser's motion, showed exponential trends, a performance plateau after 3 weeks, and a quasi-steady state performance by the end of 6 consecutive weeks.

SUBMITTER: Lee BC

PROVIDER: S-EPMC10079610 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Performing Dynamic Weight-Shifting Balance Exercises With a Smartphone-Based Wearable Telerehabilitation System for Home Use by Individuals With Parkinson's Disease: A Proof-of-Concept Study.

Lee Beom-Chan BC An Junmo J Kim Jiyeon J Lai Eugene C EC

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society 20230201

Telerehabilitation technology often helps individuals with Parkinson's disease (PD) to control their balance and improve postural stability. This proof-of-concept study describes the redesign of a smartphone-based wearable balance rehabilitation system, or Smarter Balance System (SBS) intended for in-home use, and determines the number of exercise sessions required to achieve steady-state balance exercise performance by people with PD who performed 6 weeks of in-home dynamic weight-shifting bala ...[more]

PMID: 36455080

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Project description:BackgroundBalance impairments, that lead to falls, are one of the main symptoms of Parkinson's disease (PD). Telerehabilitation is becoming more common for people with PD; however, balance is particularly challenging to assess and treat virtually. The feasibility and efficacy of virtual assessment and virtual treatment of balance in people with PD are unknown. The present study protocol has three aims: I) to determine if a virtual balance and gait assessment (instrumented L-shape mobility test) with wearable sensors can predict a gold-standard, in-person clinical assessment of balance, the Mini Balance Evaluation Systems Test (Mini-BESTest); II) to explore the effects of 12 sessions of balance telerehabilitation and unsupervised home exercises on balance, gait, executive function, and clinical scales; and III) to explore if improvements after balance telerehabilitation transfer to daily-life mobility, as measured by instrumented socks with inertial sensors worn for 7 days.MethodsThe TelePD Trial is a prospective, single-center, parallel-group, single-blind, pilot, randomized, controlled trial. This trial will enroll 80 eligible people with PD. Participants will be randomized at a 1:1 ratio into receiving home-based balance exercises in either: 1) balance telerehabilitation (experimental group, n = 40) or 2) unsupervised exercises (control group, n = 40). Both groups will perform 12 sessions of exercise at home that are 60 min long. The primary outcome will be Mini-BESTest. The secondary outcomes will be upper and lower body gait metrics from a prescribed task (instrumented L-shape mobility test); daily-life mobility measures over 7 days with wearable sensors in socks, instrumented executive function tests, and clinical scales. Baseline testing and 7 days of daily-life mobility measurement will occur before and after the intervention period.ConclusionThe TelePD Trial will be the first to explore the usefulness of using wearable sensor-based measures of balance and gait remotely to assess balance, the feasibility and efficacy of balance telerehabilitation in people with PD, and the translation of balance improvements after telerehabilitation to daily-life mobility. These results will help to develop a more effective home-based balance telerehabilitation and virtual assessment that can be used remotely in people with balance impairments.Trial registrationThis trial was prospectively registered on ClinicalTrials.gov (NCT05680597).

Project description:BackgroundFrailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0% to 59.1%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population.ObjectiveThe objective of this study was to prove that using a wearable device for assessing frailty in older home care clients could be possible.MethodsFrom June 2018 to September 2019, we recruited home care clients aged 55 years and older to be monitored over a minimum of 8 days using a wearable device. Detailed sociodemographic information and patient assessments including degree of comorbidity and activities of daily living were collected. Frailty was measured using the Fried Frailty Index. Data collected from the wearable device were used to derive variables including daily step count, total sleep time, deep sleep time, light sleep time, awake time, sleep quality, heart rate, and heart rate standard deviation. Using both wearable and conventional assessment data, multiple logistic regression models were fitted via a sequential stepwise feature selection to predict frailty.ResultsA total of 37 older home care clients completed the study. The mean age was 82.27 (SD 10.84) years, and 76% (28/37) were female; 13 participants were frail, significantly older (P<.01), utilized more home care service (P=.01), walked less (P=.04), slept longer (P=.01), and had longer deep sleep time (P<.01). Total sleep time (r=0.41, P=.01) and deep sleep time (r=0.53, P<.01) were moderately correlated with frailty. The logistic regression model fitted with deep sleep time, step count, age, and education level yielded the best predictive performance with an area under the receiver operating characteristics curve value of 0.90 (Hosmer-Lemeshow P=.88).ConclusionsWe proved that a wearable device could be used to assess frailty for older home care clients. Wearable data complemented the existing assessments and enhanced predictive power. Wearable technology can be used to identify vulnerable older adults who may benefit from additional home care services.

Project description:BackgroundAphasia is the loss or impairment of language functions and affects everyday social life. The disorder leads to the inability to understand and be understood in both written and verbal communication and affects the linguistic modalities of auditory comprehension, verbal expression, reading, and writing. Due to heterogeneity of the impairment, therapy must be adapted individually and dynamically to patient needs. An important factor for successful aphasia therapy is dose and intensity of therapy. Tablet computer-based apps are a promising treatment method that allows patients to train independently at home, is well accepted, and is known to be beneficial for patients. In addition, it has been shown to ease the burden of therapists.ObjectiveThe aim of this project was to develop an adaptive multimodal system that enables aphasic patients to train at home using language-related tasks autonomously, allows therapists to remotely assign individualized tasks in an easy and time-efficient manner, and tracks the patient's progress as well as creation of new individual exercises.MethodsThe system consists of two main parts: (1) the patient's interface, which allows the patient to exercise, and (2) the therapist's interface, which allows the therapist to assign new exercises to the patient and supervise the patient's progress. The pool of exercises is based on a hierarchical language structure. Using questionnaires, therapists and patients evaluated the system in terms of usability (ie, System Usability Scale) and motivation (ie, adapted Intrinsic Motivation Inventory).ResultsA total of 11 speech and language therapists (age: mean 28, SD 7 years) and 15 patients (age: mean 53, SD 10 years) diagnosed with aphasia participated in this study. Patients rated the Bern Aphasia App in terms of usability (scale 0-100) as excellent (score >70; Z=-1.90; P=.03) and therapists rated the app as good (score >85; Z=-1.75; P=.04). Furthermore, patients enjoyed (scale 0-6) solving the exercises (score>3; mean 3.5, SD 0.40; Z=-1.66; P=.049).ConclusionsBased on the questionnaire scores, the system is well accepted and simple to use for patients and therapists. Furthermore, the new tablet computer-based app and the hierarchical language exercise structure allow patients with different types of aphasia to train with different doses and intensities independently at home. Thus, the novel system has potential for treatment of patients with aphasia as a supplement to face-to-face therapy.

Project description:Accurate and reliable measurement of the severity of dystonia is essential for the indication, evaluation, monitoring and fine-tuning of treatments. Assessment of dystonia in children and adolescents with dyskinetic cerebral palsy (CP) is now commonly performed by visual evaluation either directly in the doctor's office or from video recordings using standardized scales. Both methods lack objectivity and require much time and effort of clinical experts. Only a snapshot of the severity of dyskinetic movements (i.e., choreoathetosis and dystonia) is captured, and they are known to fluctuate over time and can increase with fatigue, pain, stress or emotions, which likely happens in a clinical environment. The goal of this study was to investigate whether it is feasible to use home-based measurements to assess and evaluate the severity of dystonia using smartphone-coupled inertial sensors and machine learning. Video and sensor data during both active and rest situations from 12 patients were collected outside a clinical setting. Three clinicians analyzed the videos and clinically scored the dystonia of the extremities on a 0-4 scale, following the definition of amplitude of the Dyskinesia Impairment Scale. The clinical scores and the sensor data were coupled to train different machine learning models using cross-validation. The average F1 scores (0.67 ± 0.19 for lower extremities and 0.68 ± 0.14 for upper extremities) in independent test datasets indicate that it is possible to detected dystonia automatically using individually trained models. The predictions could complement standard dyskinetic CP measures by providing frequent, objective, real-world assessments that could enhance clinical care. A generalized model, trained with data from other subjects, shows lower F1 scores (0.45 for lower extremities and 0.34 for upper extremities), likely due to a lack of training data and dissimilarities between subjects. However, the generalized model is reasonably able to distinguish between high and lower scores. Future research should focus on gathering more high-quality data and study how the models perform over the whole day.

Project description:The purpose of this study was to analyze the validity, reliability, and accuracy of new wearable and smartphone-based technology for the measurement of barbell velocity in resistance training exercises. To do this, 10 highly trained powerlifters (age = 26.1 ± 3.9 years) performed 11 repetitions with loads ranging 50-100% of the 1-Repetition maximum in the bench-press, full-squat, and hip-thrust exercises while barbell velocity was simultaneously measured using a linear transducer (LT), two Beast wearable devices (one placed on the subjects' wrist -BW-, and the other one directly attached to the barbell -BB-) and the iOS PowerLift app. Results showed a high correlation between the LT and BW (r = 0.94-0.98, SEE = 0.04-0.07 m•s-1), BB (r = 0.97-0.98, SEE = 0.04-0.05 m•s-1), and the PowerLift app (r = 0.97-0.98, SEE = 0.03-0.05 m•s-1) for the measurement of barbell velocity in the three exercises. Paired samples T-test revealed systematic biases between the LT and BW, BB and the app in the hip-thrust, between the LT and BW in the full-squat and between the LT and BB in the bench-press exercise (p < 0.001). Moreover, the analysis of the linear regression on the Bland-Altman plots showed that the differences between the LT and BW (R2 = 0.004-0.03), BB (R2 = 0.007-0.01), and the app (R2 = 0.001-0.03) were similar across the whole range of velocities analyzed. Finally, the reliability of the BW (ICC = 0.910-0.988), BB (ICC = 0.922-0.990), and the app (ICC = 0.928-0.989) for the measurement of the two repetitions performed with each load were almost the same than that observed with the LT (ICC = 0.937-0.990). Both the Beast wearable device and the PowerLift app were highly valid, reliable, and accurate for the measurement of barbell velocity in the bench-press, full-squat, and hip-thrust exercises. These results could have potential practical applications for strength and conditioning coaches who wish to measure barbell velocity during resistance training.

Project description:Introduction. Time-under-tension (TUT) reflects time under load during strength training and is a proxy of the total exercise dose during strength training. The purpose of this study was to investigate if young participants are able to reproduce TUT and exercise form after two weeks of unsupervised exercises. Material and Methods. The study was an assessor-blinded intervention study with 29 participants. After an initial instruction, all participants were instructed to perform two weeks of home-based unsupervised shoulder abduction exercises three times per week with an elastic exercise band. The participants were instructed in performing an exercise with a predefined TUT (3 s concentric; 2 s isometric; 3 s eccentric; 2 s break) corresponding to a total of 240 s of TUT during three sets of 10 repetitions. After completing two weeks of unsupervised home exercises, they returned for a follow-up assessment of TUT and exercise form while performing the shoulder abduction exercise. A stretch sensor attached to the elastic band was used to measure TUT at baseline and follow-up. A physiotherapist used a pre-defined clinical observation protocol to determine if participants used the correct exercise form. Results. Fourteen of the 29 participants trained with the instructed TUT at follow-up (predefined target: 240 s ±8%). Thirteen of the 29 participants performed the shoulder abduction exercise with a correct exercise form. Seven of the 29 participants trained with the instructed TUT and exercise form at follow-up. Conclusion. The majority of participants did not use the instructed TUT and exercise form at follow-up after two weeks of unsupervised exercises. These findings emphasize the importance of clear and specific home exercise instructions if participants are to follow the given exercise prescription regarding TUT and exercise form as too many or too few exercise stimuli in relation to the initially prescribed amount of exercise most likely will provide a misinterpretation of the actual effect of any given specific home exercise intervention.

Dataset Information

Performing Dynamic Weight-Shifting Balance Exercises With a Smartphone-Based Wearable Telerehabilitation System for Home Use by Individuals With Parkinson's Disease: A Proof-of-Concept Study.

Publications

Performing Dynamic Weight-Shifting Balance Exercises With a Smartphone-Based Wearable Telerehabilitation System for Home Use by Individuals With Parkinson's Disease: A Proof-of-Concept Study.

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