AIMC Topic: Accelerometry

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Measurement of physical activity in clinical practice using accelerometers.

Journal of internal medicine Apr 16, 2019
Accelerometers are commonly used in clinical and epidemiological research for more detailed measures of physical activity and to target the limitations of self-report methods. Sensors are attached at the hip, wrist and thigh, and the acceleration dat...
Machine Learning Exercise Humans Models, Statistical Accelerometry
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Computer vision of smartphone video has potential to detect functional tremor.

Journal of the neurological sciences Apr 12, 2019
Artificial Intelligence Smartphone Video Recording Accelerometry Humans Tremor Essential Tremor
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TSE-CNN: A Two-Stage End-to-End CNN for Human Activity Recognition.

IEEE journal of biomedical and health informatics Apr 9, 2019
Human activity recognition has been widely used in healthcare applications such as elderly monitoring, exercise supervision, and rehabilitation monitoring. Compared with other approaches, sensor-based wearable human activity recognition is less affec...
Accelerometry Movement Human Activities Wearable Electronic Devices Monitoring, Ambulatory Pattern Recognition, Automated Humans Neural Networks, Computer Female Young Adult Adult Male Middle Aged
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Coarse-Fine Convolutional Deep-Learning Strategy for Human Activity Recognition.

Sensors (Basel, Switzerland) Mar 31, 2019
In the last decade, deep learning techniques have further improved human activity recognition (HAR) performance on several benchmark datasets. This paper presents a novel framework to classify and analyze human activities. A new convolutional neural ...
Humans Young Adult Sitting Position Human Activities Adult Smartphone Middle Aged Walking Deep Learning Accelerometry Photography
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Falls Risk Classification of Older Adults Using Deep Neural Networks and Transfer Learning.

IEEE journal of biomedical and health informatics Mar 27, 2019
Prior research in falls risk classification using inertial sensors has relied on the use of engineered features, which has resulted in a feature space containing hundreds of features that are likely redundant and possibly irrelevant. In this paper, w...
Signal Processing, Computer-Assisted Accelerometry Accidental Falls Adolescent ROC Curve Smartphone Adult Male Middle Aged Humans Neural Networks, Computer Female Aged Aged, 80 and over Young Adult
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Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.

Parkinsonism & related disorders Mar 26, 2019
INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkin...
Parkinson Disease Accelerometry Antiparkinson Agents Levodopa Motor Activity Middle Aged Humans Wearable Electronic Devices Female Support Vector Machine Dose-Response Relationship, Drug Aged Aged, 80 and over Male
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Baseball Player Behavior Classification System Using Long Short-Term Memory with Multimodal Features.

Sensors (Basel, Switzerland) Mar 22, 2019
In this paper, a preliminary baseball player behavior classification system is proposed. By using multiple IoT sensors and cameras, the proposed method accurately recognizes many of baseball players' behaviors by analyzing signals from heterogeneous ...
Humans Joints Photography Behavior Baseball Neural Networks, Computer Deep Learning Wearable Electronic Devices Accelerometry
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Assessment of Motor Impairments in Early Untreated Parkinson's Disease Patients: The Wearable Electronics Impact.

IEEE journal of biomedical and health informatics Mar 7, 2019
OBJECTIVE: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, mainly based on the visual inspection of motor impairments. Wearable sensors have been demonstrated to help overcoming such a difficulty, by providing obj...
Wearable Electronic Devices Monitoring, Physiologic Parkinson Disease Equipment Design Adult Male Middle Aged Signal Processing, Computer-Assisted Accelerometry Movement Humans Machine Learning Female Aged Aged, 80 and over
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A Multi-Layer Gaussian Process for Motor Symptom Estimation in People With Parkinson's Disease.

IEEE transactions on bio-medical engineering Feb 18, 2019
The assessment of Parkinson's disease (PD) poses a significant challenge, as it is influenced by various factors that lead to a complex and fluctuating symptom manifestation. Thus, a frequent and objective PD assessment is highly valuable for effecti...
Movement Wearable Electronic Devices Hypokinesia Reproducibility of Results Wrist Tremor Humans Parkinson Disease Aged Monitoring, Ambulatory Machine Learning Signal Processing, Computer-Assisted Male Accelerometry Female Middle Aged Normal Distribution
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Recognition and Repetition Counting for ComplexPhysical Exercises with Deep Learning.

Sensors (Basel, Switzerland) Feb 10, 2019
Activity recognition using off-the-shelf smartwatches is an important problem in humanactivity recognition. In this paper, we present an end-to-end deep learning approach, able to provideprobability distributions over activities from raw sensor data....
Humans Algorithms Exercise Deep Learning Sports Human Activities Wearable Electronic Devices Pattern Recognition, Automated Accelerometry
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