ArticleClinical interventions in aging2021
Predicting Sarcopenia of Female Elderly from Physical Activity Performance Measurement Using Machine Learning Classifiers.
Article in Clinical interventions in aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Sarcopenia screening based on the assessment of gait with inertial measurement units: a systematic review.BMC geriatrics · 2024Pooled it
- Machine Learning Applications and Sarcopenia.Advances in experimental medicine and biology · 2026Review
- Spine Kinematic Alterations in Nordic Walking Under Two Different Speeds of 3 and 5 km/h-A Pilot Study.Journal of functional morphology and kinesiology · 2025Article
- Development and validation of machine learning models for classifying cancer-related sarcopenia using Kinect-based mixed-reality exercises in breast cancer survivors.Translational cancer research · 2025Article
- Development of a visualized risk prediction system for sarcopenia in older adults using machine learning: a cohort study based on CHARLS.Frontiers in public health · 2025Article
- A neural network approach to sarcopenia prediction based on bioelectrical impedance in community-dwelling older adults.PloS one · 2025Article
- Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion.Diagnostics (Basel, Switzerland) · 2024Article
- Machine Learning for Movement Pattern Changes during Kinect-Based Mixed Reality Exercise Programs in Women with Possible Sarcopenia: Pilot Study.Annals of geriatric medicine and research · 2024Article
- Predicting sarcopenia in community-dwelling older adults through comprehensive physical fitness tests.BMC geriatrics · 2024Article
- Sarcopenia diagnosis using skeleton-based gait sequence and foot-pressure image datasets.Frontiers in public health · 2024Article
- Machine Learning for Sarcopenia Prediction in the Elderly Using Socioeconomic, Infrastructure, and Quality-of-Life Data.Healthcare (Basel, Switzerland) · 2023Article
- Performance Evaluation of Machine Learning Algorithms for Sarcopenia Diagnosis in Older Adults.Healthcare (Basel, Switzerland) · 2023Article
- Machine Learning Applications in Sarcopenia Detection and Management: A Comprehensive Survey.Healthcare (Basel, Switzerland) · 2023Article
- Health and Nutrition Analysis in Older Adults in San José de Minas Rural Parish in Quito, Ecuador.Global health, epidemiology and genomics · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSarcopenia is a symptom in which muscle mass decreases due to decreasing in the number of muscle fibers and muscle cross-sectional area as aging. This study aimed to develop a machine learning classification model for predicting sarcopenia through a inertial measurement unit (IMU)-based physical performance measurement data of female elderly. PATIENTS AND
methodsSeventy-eight female subjects from an elderly population (aged: 78.8±5.7 years) volunteered to participate in this study. To evaluate the physical performance of the elderly, the experiment conducted timed-up-and-go test (TUG) and 6-minute walk test (6mWT) with worn a single IMU. Based on literature review, 132 features were extracted from collected data. Feature selection was performed through the Kruskal-Wallis test, and features datasets were constructed according to feature selection. Three major machine learning-based classification algorithms classified the sarcopenia group in each dataset, and the performance of classification models was compared.
resultsAs a result of comparing the classification model performance for sarcopenia prediction, the k-nearest neighborhood algorithm (kNN) classification model using 40 major features of TUG and 6mWT showed the best performance at 88%.
conclusionThis study can be used as a basic research for the development of self-monitoring technology for sarcopenia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.