Recent Advances in Atherosclerotic Disease Screening Using Pervasive Healthcare

Luo, Jun; Yan, Zhengrong; Guo, Shuxiang; Chen, Wei

doi:10.1109/rbme.2021.3081180

Cited by 13 publications

(2 citation statements)

References 147 publications

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“…Classical machine learning methods often require large, labeled datasets for effective training, making the process cumbersome and resource-intensive [26]. To address these issues, some studies have moved towards unsupervised [27] and semi-supervised methods [28].…”

Section: Machine Learning and Emg Analysismentioning

confidence: 99%

EMG-Based Human Motion Analysis: A Novel Approach Using Towel Electrodes and Transfer Learning

Tang,

Yi,

Kumar

et al. 2024

IEEE Sensors J.

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This paper presents an innovative solution for electromyography (EMG)-based human motion analysis systems, addressing challenges of sensor comfort, inter-individual variations, and labor-intensive labeling processes. The solution combines textile towel-based electrodes with transfer learning techniques. The textile towel-based graphene/PEDOT:PSS composite electrode offers biocompatibility, low skin impedance, and user comfort, while transfer learning reduces the need for extensive new data labeling and enhances the generalisation ability of the motion analysis system. The proposed methodology achieves accurate classification of hand gestures with a minimal number of samples and epochs. This demonstrates the potential of transfer learning for efficient EMGbased human motion analysis.

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Section: Machine Learning and Emg Analysismentioning

confidence: 99%

EMG-Based Human Motion Analysis: A Novel Approach Using Towel Electrodes and Transfer Learning

Tang,

Yi,

Kumar

et al. 2024

IEEE Sensors J.

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“…Heart rate represents the number of heartbeats per minute (beat per minute, bpm), which is an effective indicator of human health [ 1 ]. There exists a high requirement for heart-rate measurement in multiple tasks such as household healthcare [ 2 , 3 ], medical treatment [ 4 ], and search and rescue [ 5 ]. Conventionally, the heart-rate measurement requires the subject to be equipped with contact measuring equipment.…”

Section: Introductionmentioning

confidence: 99%

Light and Displacement Compensation-Based iPPG for Heart-Rate Measurement in Complex Detection Conditions

Bi,

Wang,

Zhang

2024

Sensors

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A light and displacement-compensation-based iPPG algorithm is proposed in this paper for heart-rate measurement in complex detection conditions. Two compensation sub-algorithms, including light compensation and displacement compensation, are designed and integrated into the iPPG algorithm for more accurate heart-rate measurement. In the light-compensation sub-algorithm, the measurement deviation caused by the ambient light change is compensated by the mean filter-based light adjustment strategy. In the displacement-compensation sub-algorithm, the measurement deviation caused by the subject motion is compensated by the optical flow-based displacement calculation strategy. A series of heart-rate measurement experiments are conducted to verify the effectiveness of the proposed method. Compared with conventional iPPG, the average measurement accuracy increases by 3.8% under different detection distances and 5.0% under different light intensities.

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RETRACTED ARTICLE: Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process

Shivadekar

Kataria²,

Limkar³

et al. 2023

Soft Comput

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Recent Advances in Atherosclerotic Disease Screening Using Pervasive Healthcare

Cited by 13 publications

References 147 publications

EMG-Based Human Motion Analysis: A Novel Approach Using Towel Electrodes and Transfer Learning

EMG-Based Human Motion Analysis: A Novel Approach Using Towel Electrodes and Transfer Learning

Light and Displacement Compensation-Based iPPG for Heart-Rate Measurement in Complex Detection Conditions

RETRACTED ARTICLE: Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process

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