AIMC Topic: Accelerometry

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A Robust Feature Extraction Model for Human Activity Characterization Using 3-Axis Accelerometer and Gyroscope Data.

Sensors (Basel, Switzerland) Dec 7, 2020
Human Activity Recognition (HAR) using embedded sensors in smartphones and smartwatch has gained popularity in extensive applications in health care monitoring of elderly people, security purpose, robotics, monitoring employees in the industry, and o...
Humans Algorithms Discriminant Analysis Aged Accelerometry Human Activities Smartphone Support Vector Machine
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Bicycling Phase Recognition for Lower Limb Amputees Using Support Vector Machine Optimized by Particle Swarm Optimization.

Sensors (Basel, Switzerland) Nov 15, 2020
A novel method for recognizing the phases in bicycling of lower limb amputees using support vector machine (SVM) optimized by particle swarm optimization (PSO) is proposed in this paper. The method is essential for enhanced prosthetic knee joint cont...
Ankle Joint Bicycling Wireless Technology Artificial Limbs Accelerometry Algorithms Humans Lower Extremity Wearable Electronic Devices Knee Joint Support Vector Machine Amputees
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Accelerometer-Based Fall Detection Using Machine Learning: Training and Testing on Real-World Falls.

Sensors (Basel, Switzerland) Nov 13, 2020
Falling is a significant health problem. Fall detection, to alert for medical attention, has been gaining increasing attention. Still, most of the existing studies use falls simulated in a laboratory environment to test the obtained performance. We a...
Accelerometry Humans Machine Learning Algorithms Accidental Falls Support Vector Machine Monitoring, Ambulatory
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Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach.

Gait & posture Nov 10, 2020
BACKGROUND: Gait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial acceler...
Humans Machine Learning Biomechanical Phenomena Gait Gait Analysis Acceleration Foot Tibia Accelerometry
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Accelerometer-Based Human Activity Recognition for Patient Monitoring Using a Deep Neural Network.

Sensors (Basel, Switzerland) Nov 10, 2020
The objective of this study was to investigate the accuracy of a Deep Neural Network (DNN) in recognizing activities typical for hospitalized patients. A data collection study was conducted with 20 healthy volunteers (10 males and 10 females, age = 4...
Female Hospitalization Adult Humans Neural Networks, Computer Monitoring, Physiologic Posture Walking Male Middle Aged Support Vector Machine Supine Position Stair Climbing Accelerometry Human Activities
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Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method.

Neurorehabilitation and neural repair Nov 5, 2020
BACKGROUND: Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results.
Stroke Rehabilitation Stroke Accelerometry Upper Extremity Machine Learning Humans Female Adult Aged Male Middle Aged
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Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments.

Sensors (Basel, Switzerland) Oct 31, 2020
Wayfinding and navigation can present substantial challenges to visually impaired (VI) people. Some of the significant aspects of these challenges arise from the difficulty of knowing the location of a moving person with enough accuracy. Positioning ...
Accelerometry Persons with Visual Disabilities Spatial Navigation Magnetometry Humans Algorithms Neural Networks, Computer Deep Learning Smartphone
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Deep Learning to Predict Energy Expenditure and Activity Intensity in Free Living Conditions using Wrist-specific Accelerometry.

Journal of sports sciences Oct 30, 2020
Wrist-worn accelerometers are more comfortable and yield greater compliance than hip-worn devices, making them attractive for free-living activity assessments. However, intricate wrist movements may require more complex predictive models than those a...
Exercise Deep Learning Energy Metabolism Adult Male Middle Aged Humans Accelerometry Female Fitness Trackers Wrist Joint
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Development of Insert Condition Classification System for CNC Lathes Using Power Spectral Density Distribution of Accelerometer Vibration Signals.

Sensors (Basel, Switzerland) Oct 19, 2020
Insert conditions significantly influence the product quality and manufacturing efficiency of lathe machining. This study used the power spectral density distribution of the vibration signals of a lathe machining accelerometer to design an insert con...
Neural Networks, Computer Accelerometry Vibration
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Parkinson's Disease Tremor Detection in the Wild Using Wearable Accelerometers.

Sensors (Basel, Switzerland) Oct 14, 2020
Continuous in-home monitoring of Parkinson's Disease (PD) symptoms might allow improvements in assessment of disease progression and treatment effects. As a first step towards this goal, we evaluate the feasibility of a wrist-worn wearable accelerome...
Accelerometry Tremor Deep Learning Humans Wearable Electronic Devices Neural Networks, Computer Parkinson Disease
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