AIMC Topic: Accelerometry

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Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approach.

BMC public health May 7, 2024
BACKGROUND: Depression is a global burden with profound personal and economic consequences. Previous studies have reported that the amount of physical activity is associated with depression. However, the relationship between the temporal patterns of ...
Male Humans Middle Aged Machine Learning Exercise Nutrition Surveys Female Aged United States Adult Accelerometry Cross-Sectional Studies Depression Big Data Time Factors
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How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households.

Sensors (Basel, Switzerland) Apr 19, 2024
Surprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the s...
Female Animals Male Humans Machine Learning Behavior, Animal Accelerometry Pets Family Characteristics Seasons Cats
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Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks.

Sensors (Basel, Switzerland) Apr 14, 2024
The accurate estimation of energy expenditure from simple objective accelerometry measurements provides a valuable method for investigating the effect of physical activity (PA) interventions or population surveillance. Methods have been evaluated pre...
Energy Metabolism Male Linear Models Accelerometry Exercise Child Humans Neural Networks, Computer Female
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Development of a multi-wear-site, deep learning-based physical activity intensity classification algorithm using raw acceleration data.

PloS one Mar 7, 2024
BACKGROUND: Accelerometers are widely adopted in research and consumer devices as a tool to measure physical activity. However, existing algorithms used to estimate activity intensity are wear-site-specific. Non-compliance to wear instructions may le...
Child Adult Humans Wrist Exercise Accelerometry Acceleration Algorithms Deep Learning
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Measuring functional hand use in children with unilateral cerebral palsy using accelerometry and machine learning.

Developmental medicine and child neurology Mar 2, 2024
AIM: To investigate wearable sensors for measuring functional hand use in children with unilateral cerebral palsy (CP).
Hand Cerebral Palsy Accelerometry Machine Learning Female Male Humans Adolescent Wearable Electronic Devices Child
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Transforming Big Data into AI-ready data for nutrition and obesity research.

Obesity (Silver Spring, Md.) Mar 1, 2024
OBJECTIVE: Big Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), h...
Nutritional Sciences Software Biomedical Research Big Data Metabolomics Obesity Accelerometry Humans Artificial Intelligence Machine Learning
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Sleep-phasic heart rate variability predicts stress severity: Building a machine learning-based stress prediction model.

Stress and health : journal of the International Society for the Investigation of Stress Feb 27, 2024
We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self-screening in large populations. Using a Holter electrocardi...
Humans Accelerometry Electrocardiography, Ambulatory Machine Learning Heart Rate Middle Aged Female Stress, Psychological Sleep Adult Photoplethysmography Male
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An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Biosensors Feb 22, 2024
Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnosis relies on subjective lung auscultation by physicians. Enabling this capability via a low-profile,...
Respiratory Sounds Wearable Electronic Devices Humans Accelerometry Deep Learning Respiratory Rate
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Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches.

Sensors (Basel, Switzerland) Feb 8, 2024
Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we me...
Adolescent Walking Gait Accelerometry Muscular Dystrophy, Duchenne Humans Deep Learning
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Classification of human walking context using a single-point accelerometer.

Scientific reports Feb 6, 2024
Real-world walking data offers rich insights into a person's mobility. Yet, daily life variations can alter these patterns, making the data challenging to interpret. As such, it is essential to integrate context for the extraction of meaningful infor...
Humans Walking Machine Learning Accelerometry Algorithms Research Design
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