Movement Disorders and Smart Wrist Devices: A Comprehensive Study

Sensors, Journal Year: 2025, Volume and Issue: 25(1), P. 266 - 266

Published: Jan. 5, 2025

In the medical field, there are several very different movement disorders, such as tremors, Parkinson’s disease, or Huntington’s disease. A wide range of motor and non-motor symptoms characterizes them. It is evident that in modern era, use smart wrist devices, smartwatches, wristbands, bracelets spreading among all categories people. This diffusion justified by limited costs, ease use, less invasiveness (and consequently greater acceptability) than other types sensors used for health status monitoring. systematic review aims to synthesize research studies using devices a specific class disorders. Following PRISMA-S guidelines, 130 were selected analyzed. For each study, information provided relating smartwatch/wristband/bracelet model (whether it commercial not), number end-users involved experimentation stage, finally characteristics benchmark dataset possibly testing. Moreover, some articles also reported type raw data extracted from device, implemented designed algorithmic pipeline, classification methodology. turned out most have been published last ten years, showing growing interest scientific community. The mainly investigate relationship between Epilepsy seizure detection topics interest, while few papers analyzing gait Disease, ataxia, Tourette Syndrome. However, results this highlight difficulties still present identified despite advantages these technologies could bring dissemination low-cost solutions usable directly within living environments without need caregivers personnel.

Language: Английский

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At-home wearables and machine learning sensitively capture disease progression in amyotrophic lateral sclerosis

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Aug. 21, 2023

Amyotrophic lateral sclerosis causes degeneration of motor neurons, resulting in progressive muscle weakness and impairment function. Promising drug development efforts have accelerated amyotrophic sclerosis, but are constrained by a lack objective, sensitive, accessible outcome measures. Here we investigate the use wearable sensors, worn on four limbs at home during natural behavior, to quantify function disease progression 376 individuals with sclerosis. We an analysis approach that automatically detects characterizes submovements from passively collected accelerometer data produces machine-learned severity score for each limb is independent clinical ratings. show this scores progress faster than gold standard Lateral Sclerosis Functional Rating Scale-Revised (-0.86 ± 0.70 SD/year versus -0.73 0.74 SD/year), smaller trial sample size estimates (N = 76 N 121). This method offers ecologically valid scalable measure potential trials care.

Language: Английский

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Assessment of movement disorders using wearable sensors during upper limb tasks: A scoping review

Frontiers in Robotics and AI, Journal Year: 2023, Volume and Issue: 9

Published: Jan. 9, 2023

Background: Studies aiming to objectively quantify movement disorders during upper limb tasks using wearable sensors have recently increased, but there is a wide variety in described measurement and analyzing methods, hampering standardization of methods research clinics. Therefore, the primary objective this review was provide an overview sensor set-up type, included tasks, features used multiple pathological populations. The secondary identify most sensitive for detection quantification on one hand describe clinical application proposed other hand. Methods: A literature search Scopus, Web Science, PubMed performed. Articles needed meet following criteria: 1) participants were adults/children with neurological disease, 2) (at least) placed evaluation 3) comparisons between: groups with/without disorders, before/after intervention, or scale assessment disorder. 4) Outcome measures from acceleration/angular velocity signals. Results: total 101 articles included, which 56 researched Parkinson's Disease. Wrist(s), hand(s) index finger(s) popular locations. Most frequent were: finger tapping, wrist pro/supination, keeping arms extended front body finger-to-nose. frequently calculated mean, standard deviation, root-mean-square, ranges, skewness, kurtosis/entropy acceleration and/or angular velocity, combination dominant frequencies/power Examples applications automatization discrimination between patient/control group different patient groups. Conclusion: Current can support clinicians researchers selecting pathology-dependent methodologies evaluations treatment effects. Insights Disease studies accelerate development protocols remaining pathologies, provided that sufficient attention standardisation protocols, feasibility data analysis methods.

Language: Английский

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Upper limb movements as digital biomarkers in people with ALS

EBioMedicine, Journal Year: 2024, Volume and Issue: 101, P. 105036 - 105036

Published: March 1, 2024

BackgroundObjective evaluation of people with amyotrophic lateral sclerosis (PALS) in free-living settings is challenging. The introduction portable digital devices, such as wearables and smartphones, may improve quantifying disease progression hasten therapeutic development. However, there a need for tools to characterize upper limb movements neurologic disability.MethodsTwenty PALS wore wearable accelerometer, ActiGraph Insight Watch, on their wrist six months. They also used Beiwe, smartphone application that collected self-entry ALS Functional Rating Scale—Revised (ALSFRS-RSE) survey responses every 1–4 weeks. We developed several measures quantify count duration movements: flexion, extension, supination, pronation. New were compared against ALSFRS-RSE total score (Q1–12), individual specific questions related handwriting (Q4), cutting food (Q5), dressing performing hygiene (Q6), turning bed adjusting clothes (Q7). Additional analysis considered activity counts (TAC).FindingsAt baseline, higher Q1–12 performed more movements, these faster individuals advanced disease. Most movement metrics had statistically significant change over time, indicating declining function either by decreasing or increasing metric. All significantly associated Q1–12, flexion extension Q6 Q7, supination pronation Q4. Q7. retained statistical significance after TAC.InterpretationWearable accelerometer data can be generate biomarkers facilitate patient monitoring environments. presented method offers interpretable patients' functioning versatile tracking the interest.FundingMitsubishi-Tanabe Pharma Holdings America, Inc.

Language: Английский

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Accelerometer-based measures in Friedreich ataxia: a longitudinal study on real-life activity

Frontiers in Pharmacology, Journal Year: 2024, Volume and Issue: 15

Published: March 19, 2024

Quantitative measurement of physical activity may complement neurological evaluation and provide valuable information on patients’ daily life. We evaluated longitudinal changes in patients with Friedreich ataxia (FRDA) using remote monitoring wearable sensors. performed an observational study 26 adult FRDA 13 age-sex matched healthy controls (CTR). Participants were asked to wear two sensors, at non-dominant wrist waist, for 7 days during waking hours. Evaluations baseline 1-year follow-up. analysed the percentage time spent sedentary or activities, Vector Magnitude 3 axes (VM3), average number steps/min. Study participants also clinical scales functional tests upper limbs dexterity walking capability. Baseline data showed that had overall reduced level as compared CTR. Accelerometer-based measures highly correlated disease duration FRDA. Significantly from l-year follow-up observed following measures: (i) VM3; (ii) light activity, (iii) Moderate-Vigorous Physical Activity (MVPA). Reduction corresponded worsening gait score Scale Assessment Rating Ataxia. Real-life is feasible well tolerated by patients. can quantify progression over 1 year, providing objective about patient’s motor activities supporting usefulness these complementary outcome measure interventional trials.

Language: Английский

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Wearable sensors in paediatric neurology

Developmental Medicine & Child Neurology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

Wearable sensors have the potential to transform diagnosis, monitoring, and management of children who neurological conditions. Traditional methods for assessing disorders rely on clinical scales subjective measures. The snapshot disease progression at a particular time point, lack cooperation by during assessments, susceptibility bias limit utility these sensors, which capture data continuously in natural settings, offer non-invasive objective alternative traditional methods. This review examines role wearable various paediatric conditions, including cerebral palsy, epilepsy, autism spectrum disorder, attention-deficit/hyperactivity as well Rett syndrome, Down Angelman Prader-Willi neuromuscular such Duchenne muscular dystrophy spinal atrophy, ataxia, Gaucher disease, headaches, sleep disorders. highlights their application tracking motor function, seizure activity, daily movement patterns gain insights into therapeutic response. Although challenges related population size, compliance, ethics, regulatory approval remain, technology promises improve trials outcomes patients neurology.

Language: Английский

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The use of digital devices to monitor physical behaviour in motor neuron disease: a systematic review (Preprint)

Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: 27, P. e68479 - e68479

Published: March 1, 2025

Background Motor neuron disease (MND) is a progressive and incurable neurodegenerative disease. The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) the primary clinical tool for assessing severity progression in MND. However, despite its widespread use, it does not adequately capture extent of physical function decline. There an urgent need sensitive measures that can be used to robustly evaluate new treatments. Measures derived from digital devices are beginning assess progression. value establishing consensus approach standardizing use such devices. Objective We aimed explore how being quantify free-living behavior evaluated feasibility assessed implications monitoring future trials practice. Methods Systematic searches 4 databases were performed October 2023 June 2024. Peer-reviewed English-language articles (including preprints) examined people living with MND their included. Study reporting quality was using 22-item checklist (maximum possible score=44 points). Results In total, 12 met inclusion criteria data extraction. All studies longitudinal observational design, but collection, analysis, protocols varied. Quality assessment scores ranged between 19 40 points. Sample sizes 10 376 at baseline, declining over course study. Most accelerometer device worn on wrist, chest, hip, or ankle. Participants typically asked continuously wear 1 8 days 1- 4-month intervals, running weeks 24 months. Some participants full duration. Studies traditional end points focusing duration, intensity, frequency activity nontraditional features individual’s movement patterns. correlation coefficients (r) ALSFRS-R 0.31 0.78. Greater frequencies improved point sensitivity shown provide smaller sample size requirements shorter durations hypothetical trials. People found acceptable reported low burden. Adherence (67%) good, ranging approximately 86% 96%, differences evident locations. perspectives other users practice explored. Conclusions Remote infancy has potential function. It essential develop statement, working toward agreed standardized methods reporting.

Language: Английский

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Biological kinematics: a detailed review of the velocity-curvature power law calculation

Experimental Brain Research, Journal Year: 2025, Volume and Issue: 243(5)

Published: April 3, 2025

Language: Английский

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Real-life ankle submovements and computer mouse use reflect patient-reported function in adult ataxias

Brain Communications, Journal Year: 2023, Volume and Issue: 5(2)

Published: March 2, 2023

Novel disease-modifying therapies are being evaluated in spinocerebellar ataxias and multiple system atrophy. Clinician-performed disease rating scales relatively insensitive for measuring change over time, resulting large long clinical trials. We tested the hypothesis that sensors worn continuously at home during natural behaviour a web-based computer mouse task performed could produce interpretable, meaningful reliable motor measures potential use Thirty-four individuals with degenerative (spinocerebellar ataxia types 1, 2, 3 6 atrophy of cerebellar type) eight age-matched controls completed cross-sectional study. Participants wore an ankle wrist sensor 1 week Hevelius times 4 weeks. examined properties primitives called 'submovements' derived from continuous wearable clicks trajectories relationship to patient-reported function (Patient-Reported Outcome Measure Ataxia) (Scale Assessment Rating Ataxia Brief Scale). The test-retest reliability digital differences between control participants were evaluated. Individuals had smaller, slower less powerful submovements home. A composite measure based on strongly correlated scale scores (Pearson's r = 0.82-0.88), self-reported (r 0.81), high (intraclass correlation coefficient 0.95) distinguished participants, including preataxic (n 4) controls. movements total 0.86-0.88) arm 0.65-0.75), well 0.72-0.73) 0.99). These data indicate highly can be obtained measurement movement, particularly location, simple point-and-click This study supports these two inexpensive easy-to-use technologies longitudinal history studies type shows promise as outcome interventional

Language: Английский

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Sensitive Quantification of Cerebellar Speech Abnormalities Using Deep Learning Models

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 62328 - 62340

Published: Jan. 1, 2024

Objective, sensitive, and meaningful disease assessments are critical to support clinical trials care. Speech changes one of the earliest most evident manifestations cerebellar ataxias. This work aims develop models that can accurately identify quantify signs ataxic speech. We use convolutional neural networks capture motor speech phenotype ataxia based on time frequency partial derivatives log-mel spectrogram representations train classification distinguish patients with from healthy controls as well regression estimate severity. Classification were able individuals ataxia, including participants who clinicians rated having no detectable deficits in Regression produced accurate estimates severity, measure subclinical captured progression over time. Convolutional trained signal detect sub-clinical ataxias sensitively change Learned analysis have potential aid early detection provide low-burden assessment tools neurological

Language: Английский

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