AI Medical Compendium Topic:
Wearable Electronic Devices

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The electrocardiogram endeavour: from the Holter single-lead recordings to multilead wearable devices supported by computational machine learning algorithms.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
This review aims to provide a comprehensive recapitulation of the evolution in the field of cardiac rhythm monitoring, shedding light in recent progress made in multilead ECG systems and wearable devices, with emphasis on the promising role of the ar...

Artificial neural networks-based classification of emotions using wristband heart rate monitor data.

Medicine
Heart rate variability (HRV) is an objective measure of emotional regulation. This study aimed to estimate the accuracy with which an artificial neural network (ANN) algorithm could classify emotions using HRV data that were obtained using wristband ...

Estimating Movements of Human Body for the Shirt-Type Wearable Device Mounted on the Strain Sensors Based on Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
To measure the life log of humans and enjoy virtual or augmented reality video games, several wearable devices have been developed that allow users to intuitively input commands. However, monitoring and estimating three-dimensional human motions for ...

Classification of Rehabilitation Participation in Elderly In-patients with Mild Cognitive Impairments Utilizing Physiological Responses.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study investigated the possibility of utilising physiological responses and machine learning techniques to determine the degree of participation of in-patients with mild cognitive impairment at rehabilitation institutions. Physiological signals ...

Wearable Sensors for Prodromal Motor Assessment of Parkinson's Disease using Supervised Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. Idiopathic hyposmia (IH), a reduced olfactory sensitivity, is a preclinical marker for the pathology and affects >95% of PD patie...

Feasibility Study of Deep Neural Network for Heart Rate Estimation from Wearable Photoplethysmography and Acceleration Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Heart rate (HR) estimation using wearable reflectance-type photoplethysmographic (PPG) signals is challenging due to low signal-to-noise ratio (SNR). Especially during intensive exercise, motion artifacts (MAs) overwhelm PPG signals in an unpredictab...

Prediction of Plantar Forces During Gait Using Wearable Sensors and Deep Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
To enable on-time and high-fidelity lower-limb exoskeleton control, it is effective to predict the future human motion from the observed status. In this research, we propose a novel method to predict future plantar force during the gait using IMU and...

Deep Neural Network-Based Gait Classification Using Wearable Inertial Sensor Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Human gait has been regarded as a useful behavioral biometric trait for personal identification and authentication. This study aimed to propose an effective approach for classifying gait, measured using wearable inertial sensors, based on neural netw...

Deep Learning based Gait Abnormality Detection using Wearable Sensor System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Gait is an extraordinary complex function of human body that involves the activation of entire visceral nervous system, making human gait definite to various functional abnormalities. Diagnosis and treatment of such disorders prior to their developme...

Categorizing Sleep in Older Adults with Wireless Activity Monitors Using LSTM Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Novel approaches are needed to accurately classify and monitor sleep patterns in older adults, particularly those with cognitive impairment and non-normative sleep. Traditional methods ignore underlying sleep architecture in these patient populations...