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Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

ABSTRACT: Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this regard can provide a reliable and economical means of tracking such activities, and such sensors are readily available in smartphones and watches. This study is the first of its kind to develop a wearable sensor-based physical activity classification system using a special class of supervised machine learning approaches called boosting algorithms. The study presents the performance analysis of several boosting algorithms (extreme gradient boosting-XGB, light gradient boosting machine-LGBM, gradient boosting-GB, cat boosting-CB and AdaBoost) in a fair and unbiased performance way using uniform dataset, feature set, feature selection method, performance metric and cross-validation techniques. The study utilizes the Smartphone-based dataset of thirty individuals. The results showed that the proposed method could accurately classify the activities of daily living with very high performance (above 90%). These findings suggest the strength of the proposed system in classifying activity of daily living using only the smartphone sensor's data and can assist in reducing the physical inactivity patterns to promote a healthier lifestyle and wellbeing.

SUBMITTER: Rahman S

PROVIDER: S-EPMC7038216 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

Rahman Saifur S Irfan Muhammad M Raza Mohsin M Moyeezullah Ghori Khawaja K Yaqoob Shumayla S Awais Muhammad M

International journal of environmental research and public health 20200208 3

Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this regard can provide a reliable and economical means of tracking such activities, and such sensors are readily available in smartphones and watches. This study is the first of its kind to develop a wearable sensor-based physical activity classificatio ...[more]

PMID: 32046302

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Project description:Background Activities of daily living (ADLs) and instrumental activities of daily living (IADLs) are essential for independent living and are predictors of morbidity and mortality in older populations. Older adults who are dependent in ADLs and IADLs are also more likely to have poor muscle measures defined as low muscle mass, muscle strength, and physical performance, which further limit their ability to perform activities. The aim of this systematic review and meta-analysis was to determine if muscle measures are predictive of ADL and IADL in older populations. Methods A systematic search was conducted using four databases (MEDLINE, EMBASE, Cochrane, and CINAHL) from date of inception to 7 June 2018. Longitudinal cohorts were included that reported baseline muscle measures defined by muscle mass, muscle strength, and physical performance in conjunction with prospective ADL or IADL in participants aged 65 years and older at follow-up. Meta-analyses were conducted using a random effect model. Results Of the 7760 articles screened, 83 articles were included for the systematic review and involved a total of 108 428 (54.8% female) participants with a follow-up duration ranging from 11 days to 25 years. Low muscle mass was positively associated with ADL dependency in 5/9 articles and 5/5 for IADL dependency. Low muscle strength was associated with ADL dependency in 22/34 articles and IADL dependency in 8/9 articles. Low physical performance was associated with ADL dependency in 37/49 articles and with IADL dependency in 9/11 articles. Forty-five articles were pooled into the meta-analyses, 36 reported ADL, 11 reported IADL, and 2 reported ADL and IADL as a composite outcome. Low muscle mass was associated with worsening ADL (pooled odds ratio (95% confidence interval) 3.19 (1.29-7.92)) and worsening IADL (1.28 (1.02-1.61)). Low handgrip strength was associated with both worsening ADL and IADL (1.51 (1.34-1.70); 1.59 (1.04-2.31) respectively). Low scores on the short physical performance battery and gait speed were associated with worsening ADL (3.49 (2.47-4.92); 2.33 (1.58-3.44) respectively) and IADL (3.09 (1.06-8.98); 1.93 (1.69-2.21) respectively). Low one leg balance (2.74 (1.31-5.72)), timed up and go (3.41 (1.86-6.28)), and chair stand test time (1.90 (1.63-2.21)) were associated with worsening ADL. Conclusions Muscle measures at baseline are predictors of future ADL and IADL dependence in the older adult population.

Project description:BackgroundCardiac arrhythmias are common conditions in older people. Unfortunately, there is limited literature on associations between cardiac arrhythmias and physical performance or disability. We therefore aimed to prospectively investigate associations between cardiac arrhythmias and changes in disability and physical performance during 8 years of follow-up, using data from the Italian Longitudinal Study on Aging (ILSA).MethodsCardiac arrhythmias diagnosis was posed through a screening phase, confirmed by a physician. The onset of disability in activities of daily living (ADL) and the changes in several physical performance tests during follow-up were considered as outcomes. Fully-adjusted and propensity-score Cox Proportional Hazard models and mixed models were used for exploring associations between cardiac arrhythmia and the outcomes of interest.ResultsThe prevalence of cardiac arrhythmia at baseline was 23.3%. People reporting cardiac arrhythmia at the baseline were significantly older, more frequently male, smokers and reported a higher presence of all medical conditions investigated (hypertension, heart failure, angina, myocardial infarction, diabetes, stroke), but no difference in dementia, Parkinsonism, cognitive or mood disorder. Cardiac arrhythmia at baseline was significantly associated with the incidence of disability in ADL (HR = 1.23; 95%: CI: 1.01-1.50; P = 0.0478 in propensity score analyses; HR = 1.28; 95% CI: 1.01-1.61; P = 0.0401 in fully adjusted models). Cardiac arrhythmia at baseline was also associated with a significant worsening in balance test (P = 0.0436).ConclusionsThe presence of cardiac arrhythmia at baseline was associated with a significant higher risk of disability and of worsening in some physical performance tests, particularly those relating to balance. Screening and frequently assessing physical performance in older people affected by cardiac arrhythmia can be important to prevent a loss of physical performance, with further, potential, complications of medical management.

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Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

Publications

Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

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