AIMC Topic: Accelerometry

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Multi-Activity Step Counting Algorithm Using Deep Learning Foot Flat Detection with an IMU Inside the Sole of a Shoe.

Sensors (Basel, Switzerland) Oct 29, 2024
Step counting devices were previously shown to be efficient in a variety of applications such as athletic training or patient's care programs. Various sensor placements and algorithms were previously experimented, with a best mean absolute percentage...
Algorithms Female Young Adult Adult Humans Running Accelerometry Foot Shoes Male Middle Aged Deep Learning Walking
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Wearable-Enabled Algorithms for the Estimation of Parkinson's Symptoms Evaluated in a Continuous Home Monitoring Setting Using Inertial Sensors.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Oct 29, 2024
Motor symptoms such as tremor and bradykinesia can develop concurrently in Parkinson's disease; thus, the ideal home monitoring system should be capable of tracking symptoms continuously despite background noise from daily activities. The goal of thi...
Hypokinesia Tremor Male Dyskinesias Middle Aged Video Recording Female Wearable Electronic Devices Monitoring, Ambulatory Humans Parkinson Disease Reproducibility of Results Accelerometry Equipment Design Aged Machine Learning Feasibility Studies Sensitivity and Specificity Algorithms Activities of Daily Living
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Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation.

Physiological measurement Sep 26, 2024
This study aimed to develop convolutional neural networks (CNNs) models to predict the energy expenditure (EE) of children from raw accelerometer data. Additionally, this study sought to external validation of the CNN models in addition to the linear...
Child, Preschool Child Energy Metabolism Accelerometry Neural Networks, Computer Humans Machine Learning Female Male
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Personalized food consumption detection with deep learning and Inertial Measurement Unit sensor.

Computers in biology and medicine Sep 25, 2024
For individuals diagnosed with diabetes mellitus, it is crucial to keep a record of the carbohydrates consumed during meals, as this should be done at least three times daily, amounting to an average of six meals. Unfortunately, many individuals tend...
Humans Male Deep Learning Diabetes Mellitus Accelerometry
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Characterizing daily physical activity patterns with unsupervised learning via functional mixture models.

Journal of behavioral medicine Sep 21, 2024
Physical inactivity is a significant public health concern. Consideration of inter-individual variations in physical activity (PA) trends can provide additional information about the groups under study to aid intervention design. This study aims to i...
Accelerometry Young Adult Humans Sedentary Behavior Adult Phenotype Male Exercise Female Middle Aged Cluster Analysis Aged Unsupervised Machine Learning Bayes Theorem
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The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Dogs (): A Validation Study.

Sensors (Basel, Switzerland) Sep 13, 2024
Assessing the behaviour and physical attributes of domesticated dogs is critical for predicting the suitability of animals for companionship or specific roles such as hunting, military or service. Common methods of behavioural assessment can be time ...
Machine Learning Dogs Behavior, Animal Locomotion Accelerometry Algorithms Female Animals Male
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Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults.

Scientific reports Sep 6, 2024
Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Her...
Middle Aged Wearable Electronic Devices Wrist Gait Aged Aged, 80 and over Male Supervised Machine Learning Activities of Daily Living Accelerometry Humans Algorithms Female
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Enhancing Heart Failure Care: Deep Learning-Based Activity Classification in Left Ventricular Assist Device Patients.

ASAIO journal (American Society for Artificial Internal Organs : 1992) Sep 4, 2024
Accurate activity classification is essential for the advancement of closed-loop control for left ventricular assist devices (LVADs), as it provides necessary feedback to adapt device operation to the patient's current state. Therefore, this study ai...
Heart-Assist Devices Accelerometry Aged Middle Aged Adult Humans Deep Learning Male Neural Networks, Computer Heart Failure Female Heart Rate
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Deep Learning-Based Obesity Identification System for Young Adults Using Smartphone Inertial Measurements.

International journal of environmental research and public health Sep 4, 2024
Obesity recognition in adolescents is a growing concern. This study presents a deep learning-based obesity identification framework that integrates smartphone inertial measurements with deep learning models to address this issue. Utilizing data from ...
Adolescent Smartphone Obesity Young Adult Gait Humans Adult Accelerometry Neural Networks, Computer Male Female Deep Learning
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Speech synthesis from three-axis accelerometer signals using conformer-based deep neural network.

Computers in biology and medicine Sep 3, 2024
Silent speech interfaces (SSIs) have emerged as innovative non-acoustic communication methods, and our previous study demonstrated the significant potential of three-axis accelerometer-based SSIs to identify silently spoken words with high classifica...
Neural Networks, Computer Female Young Adult Adult Humans Accelerometry Male Speech Signal Processing, Computer-Assisted
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