Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079376
Hossein Kavianirad, Satoshi Endo, T. Keller, S. Hirche
Functiona1 electrical stimulation (FES) applies electrical pulses to muscle fibers through the skin for assisting functional movements in patients with motor disability. Muscle activity feedback such as volitional Electromyography (vEMG) can optimize the performance of the FES system in both rehabilitation or activity of daily living (ADL), however, artifacts caused by simultaneous use of FES and EMG on the same muscles contaminate the EMG signal. This paper, using an adaptive filter, aims to investigate the estimation of the volitional torque from filtered vEMG. Based on this estimation, the usability and performance of the adaptive filter for estimating volitional torque are studied on 5 healthy participants and we show that this filter can be used for volitional torque estimation. In the next step, it is shown how this map can be used in closed-loop FES control for estimating volitional torque.
{"title":"EMG-Based Volitional Torque Estimation in Functional Electrical Stimulation Control","authors":"Hossein Kavianirad, Satoshi Endo, T. Keller, S. Hirche","doi":"10.1109/IECBES54088.2022.10079376","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079376","url":null,"abstract":"Functiona1 electrical stimulation (FES) applies electrical pulses to muscle fibers through the skin for assisting functional movements in patients with motor disability. Muscle activity feedback such as volitional Electromyography (vEMG) can optimize the performance of the FES system in both rehabilitation or activity of daily living (ADL), however, artifacts caused by simultaneous use of FES and EMG on the same muscles contaminate the EMG signal. This paper, using an adaptive filter, aims to investigate the estimation of the volitional torque from filtered vEMG. Based on this estimation, the usability and performance of the adaptive filter for estimating volitional torque are studied on 5 healthy participants and we show that this filter can be used for volitional torque estimation. In the next step, it is shown how this map can be used in closed-loop FES control for estimating volitional torque.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123220595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079434
Thi Hong Mân Vu, S. Morozkina, M. Uspenskaya, R. Olekhnovich
Nanofibers attract attention due to the possibility of varying their properties over a wide range when changing the technical parameters of their production. Polyvinyl alcohol (PVA) nanofibers are one of the most important considerations, not only because of their nano size, which helps to reduce device size, but also because of the benefits of biosafety, biodegradability and their abundant raw materials. Particular attention is drawn to the possibility of electrospinning fibers from PVA solutions in a mixture of solvents. This makes it possible to load PVA fibers with various active molecules, including those that do not dissolve in water. This study focuses on the fabrication of electrospun PVA nanofibers from an aqueous PVA-acetic acid solution. The addition of acetic acid to the electrospinning process had no effect on the chemical nature of the resulting nanofiber system, however significantly improved its quality. The electrospun PVA nanofiber diameter was substantially reduced from 170 ± 28 nm to 114 ± 31 nm by the addition of 35 percent (w/w) acetic acid in the aqueous solution of PVA. The mechanical strength, in particular, was observed to increase as the acetic acid concentration in the electrospinning solution increased.
{"title":"Fabrication of Polyvinyl Alcohol Nanofibers for the Delivery of Biologically Active Molecules","authors":"Thi Hong Mân Vu, S. Morozkina, M. Uspenskaya, R. Olekhnovich","doi":"10.1109/IECBES54088.2022.10079434","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079434","url":null,"abstract":"Nanofibers attract attention due to the possibility of varying their properties over a wide range when changing the technical parameters of their production. Polyvinyl alcohol (PVA) nanofibers are one of the most important considerations, not only because of their nano size, which helps to reduce device size, but also because of the benefits of biosafety, biodegradability and their abundant raw materials. Particular attention is drawn to the possibility of electrospinning fibers from PVA solutions in a mixture of solvents. This makes it possible to load PVA fibers with various active molecules, including those that do not dissolve in water. This study focuses on the fabrication of electrospun PVA nanofibers from an aqueous PVA-acetic acid solution. The addition of acetic acid to the electrospinning process had no effect on the chemical nature of the resulting nanofiber system, however significantly improved its quality. The electrospun PVA nanofiber diameter was substantially reduced from 170 ± 28 nm to 114 ± 31 nm by the addition of 35 percent (w/w) acetic acid in the aqueous solution of PVA. The mechanical strength, in particular, was observed to increase as the acetic acid concentration in the electrospinning solution increased.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132526931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079410
S. Manna, M. A. Hannan, B. Azhar, Danny D Smith, Tasmina Islam
Over fourteen million people suffer from neuromuscular diseases in the UK such as strokes, spinal cord injuries, and Parkinson’s disease etc. That means at least one in six people in the UK are living with one or more neurological conditions. In order for patients to return to normal life sooner, a rigorous rehabilitation process is needed. In hospitals, physiotherapists and neurological experts prescribe specific neurorehabilitation exercises. In most cases, patients need to schedule an appointment to receive treatment in a hospital or to have physiotherapists visit them at home. The number of neuromuscular patients has increased, resulting in longer hospital waiting times. In particular, during COVID-19, patients were not allowed to visit hospitals or have physiotherapists visit them due to government restrictions. Online guides for personalised and custom rehabilitation therapy for joint spasticity and stiffness are also not available. This paper reports the development of an IoT-based prototype system that monitors and records joint movements using sensory footwear (consisting of FSR and IMU sensors) and Kinect sensors. In addition, a prototype web portal is also being developed to record performance data during exercises at home and interact with clinicians remotely. A pilot study has been conducted with six healthy individuals and test results show that there is a strong correlation between Kinect data and FSR data in terms of coordination between joint movements.
{"title":"A Smart and Home-based Telerehabilitation Tool for Patients with Neuromuscular Disorder","authors":"S. Manna, M. A. Hannan, B. Azhar, Danny D Smith, Tasmina Islam","doi":"10.1109/IECBES54088.2022.10079410","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079410","url":null,"abstract":"Over fourteen million people suffer from neuromuscular diseases in the UK such as strokes, spinal cord injuries, and Parkinson’s disease etc. That means at least one in six people in the UK are living with one or more neurological conditions. In order for patients to return to normal life sooner, a rigorous rehabilitation process is needed. In hospitals, physiotherapists and neurological experts prescribe specific neurorehabilitation exercises. In most cases, patients need to schedule an appointment to receive treatment in a hospital or to have physiotherapists visit them at home. The number of neuromuscular patients has increased, resulting in longer hospital waiting times. In particular, during COVID-19, patients were not allowed to visit hospitals or have physiotherapists visit them due to government restrictions. Online guides for personalised and custom rehabilitation therapy for joint spasticity and stiffness are also not available. This paper reports the development of an IoT-based prototype system that monitors and records joint movements using sensory footwear (consisting of FSR and IMU sensors) and Kinect sensors. In addition, a prototype web portal is also being developed to record performance data during exercises at home and interact with clinicians remotely. A pilot study has been conducted with six healthy individuals and test results show that there is a strong correlation between Kinect data and FSR data in terms of coordination between joint movements.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123181412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079630
C. Tan, Wei-Xin Hiu, Nurulhasanah Mazlan, Pei-Gie Loh, Xu-Ning Kong, W. Liow, Y. Z. Chong, Choon-Hian Goh
Due to the pandemic, there is high utilization of certain medical resources and a shortage of pharmaceuticals. Hence, this project aims to design and construct a web application that can connect the Malaysian community with healthcare facilities in order to facilitate medical resource sharing. This platform contains the following functionalities: Registration, My Account, Log In, Donation and Request Submission, Donation and Request Listings, My Donation and My Request, Statistics Dashboards and Center of Information. The web application was developed on the Velo by Wix development platform using tools such as applications, APIs and databases provided by Velo. Once construction was completed, a pilot study was conducted for 3 weeks using a digital questionnaire that had 5 main sections: demographics, digital literacy assessment, aesthetics evaluation, user experience and new functionality suggestions. This study garnered a total of 41 respondents. Then, descriptive analysis and inferential analysis using Chi-Square Test of Independents and Mann-Whitney U Test were carried out on the results obtained from the pilot study. Lastly, the results from the pilot survey found that this platform was aesthetically appealing and the performance of the functionalities provided were satisfactory.Clinical Relevance– This project provides a platform that facilitates the donation of medical resources to healthcare facilities to alleviate the burden caused by medical resource shortages.
{"title":"Development of a Digital Resources Sharing Platform for the Hospitals in Malaysia","authors":"C. Tan, Wei-Xin Hiu, Nurulhasanah Mazlan, Pei-Gie Loh, Xu-Ning Kong, W. Liow, Y. Z. Chong, Choon-Hian Goh","doi":"10.1109/IECBES54088.2022.10079630","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079630","url":null,"abstract":"Due to the pandemic, there is high utilization of certain medical resources and a shortage of pharmaceuticals. Hence, this project aims to design and construct a web application that can connect the Malaysian community with healthcare facilities in order to facilitate medical resource sharing. This platform contains the following functionalities: Registration, My Account, Log In, Donation and Request Submission, Donation and Request Listings, My Donation and My Request, Statistics Dashboards and Center of Information. The web application was developed on the Velo by Wix development platform using tools such as applications, APIs and databases provided by Velo. Once construction was completed, a pilot study was conducted for 3 weeks using a digital questionnaire that had 5 main sections: demographics, digital literacy assessment, aesthetics evaluation, user experience and new functionality suggestions. This study garnered a total of 41 respondents. Then, descriptive analysis and inferential analysis using Chi-Square Test of Independents and Mann-Whitney U Test were carried out on the results obtained from the pilot study. Lastly, the results from the pilot survey found that this platform was aesthetically appealing and the performance of the functionalities provided were satisfactory.Clinical Relevance– This project provides a platform that facilitates the donation of medical resources to healthcare facilities to alleviate the burden caused by medical resource shortages.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122064191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079671
Yee Shuang Ng, S. Chan, J. Loo, Yin Qing Tan
Muscular function adaptations and movement capacities differ among individuals. However, there is uncertainty about squat depth and squat-jump performance. Hence, the study aimed to investigate the effect of knee flexion angle on the squat jump performance. 15 Asian females $(24pm 2$ years, $163pm 3mathrm{c}mathrm{m}$, and $54pm 5mathrm{k}mathrm{g}$) performed squat jumps at the knee flexion angle of $60^{circ}, 75^{circ}, 90^{circ}$, 1050, and 1200. Flight time, peak speed, peak propulsive force, maximum concentric power, and flight height during the propulsive phase were measured using the BTS G-Walk® system. The results revealed that increasing knee flexion angle corresponded to a significant decrease in flight time, peak speed, and flight height but an increase in propulsive peak force $(plt .05)$. The highest maximum concentric power was observed at 750. Flight time $(r^{2}=.854, plt .05)$ and peak speed $(r^{2}=.849,plt 05)$ were significantly correlated to flight height. Results indicated that optimal squat jump performance was observed at the knee flexion angle of600 while flight time and peak speed were good predictors of squat jump performance.
{"title":"Effect of Knee Flexion Angle on Squat Jump Performance","authors":"Yee Shuang Ng, S. Chan, J. Loo, Yin Qing Tan","doi":"10.1109/IECBES54088.2022.10079671","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079671","url":null,"abstract":"Muscular function adaptations and movement capacities differ among individuals. However, there is uncertainty about squat depth and squat-jump performance. Hence, the study aimed to investigate the effect of knee flexion angle on the squat jump performance. 15 Asian females $(24pm 2$ years, $163pm 3mathrm{c}mathrm{m}$, and $54pm 5mathrm{k}mathrm{g}$) performed squat jumps at the knee flexion angle of $60^{circ}, 75^{circ}, 90^{circ}$, 1050, and 1200. Flight time, peak speed, peak propulsive force, maximum concentric power, and flight height during the propulsive phase were measured using the BTS G-Walk® system. The results revealed that increasing knee flexion angle corresponded to a significant decrease in flight time, peak speed, and flight height but an increase in propulsive peak force $(plt .05)$. The highest maximum concentric power was observed at 750. Flight time $(r^{2}=.854, plt .05)$ and peak speed $(r^{2}=.849,plt 05)$ were significantly correlated to flight height. Results indicated that optimal squat jump performance was observed at the knee flexion angle of600 while flight time and peak speed were good predictors of squat jump performance.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122426437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079443
Ahmed Faozi Ahmed Rabea, Siti Anom Ahmad, S. Jantan, A. C. Soh, A. J. Ishak, Raja Nurzatul Efah Raja Adnan, N. Al-Qazzaz
One of the major reasons for road accidents is driver’s fatigue which causes several fatalities every year. Various studies on road accidents have proved that 20% of the accidents are caused mainly due to fatigue among drivers while driving. This paper presents the use of deep learning technique in classifying fatigue in drivers. By using deep neural networks, features are extracted automatically from preprocessed data of physiological signals such as electrocardiogram, heart rate, skin conductance response and body temperature. Public dataset HciLAB was used to train and validate the classification model. In this work, a comparative analysis of using Recurrent Neural Network - Long Short-term Memory (RNN-LSTM) deep learning architecture and the standard artificial neural network (ANN) was proposed and developed to classify fatigue based on the physiological features of the driver. The results revealed the superiority RNN-LSTM (98%) over standard ANN (80%), for driver fatigue classification. The proposed methods, based on RNN-LSTM deep learning architecture introduced elevated average accuracy in comparison with the standard artificial neural network.
{"title":"Driver’s Fatigue Classification based on Physiological Signals Using RNN-LSTM Technique","authors":"Ahmed Faozi Ahmed Rabea, Siti Anom Ahmad, S. Jantan, A. C. Soh, A. J. Ishak, Raja Nurzatul Efah Raja Adnan, N. Al-Qazzaz","doi":"10.1109/IECBES54088.2022.10079443","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079443","url":null,"abstract":"One of the major reasons for road accidents is driver’s fatigue which causes several fatalities every year. Various studies on road accidents have proved that 20% of the accidents are caused mainly due to fatigue among drivers while driving. This paper presents the use of deep learning technique in classifying fatigue in drivers. By using deep neural networks, features are extracted automatically from preprocessed data of physiological signals such as electrocardiogram, heart rate, skin conductance response and body temperature. Public dataset HciLAB was used to train and validate the classification model. In this work, a comparative analysis of using Recurrent Neural Network - Long Short-term Memory (RNN-LSTM) deep learning architecture and the standard artificial neural network (ANN) was proposed and developed to classify fatigue based on the physiological features of the driver. The results revealed the superiority RNN-LSTM (98%) over standard ANN (80%), for driver fatigue classification. The proposed methods, based on RNN-LSTM deep learning architecture introduced elevated average accuracy in comparison with the standard artificial neural network.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131523000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079417
Thomas Gänzle, Clemens Klöck, Karsten Heuschkel
This work focused on vital sign monitoring of a sleeping subject in real-time using the AWR1642 Boost of Texas Instruments. A newly designed signal processing chain is proposed to obtain a clearly recognizable heart and breath signal from the raw radar data. The averaged breath and heart rates were then calculated from these breath and heart signals. For the evaluation of these frequencies, the pulse of the test person was measured parallel to the radar measurement with a Garmin Forerunner 735XT. The results of the research show, that it would be possible to implement a monitoring system with the help of a radar sensor.
{"title":"Real-Time Vital Sign Detection using a 77 GHz FMCW Radar","authors":"Thomas Gänzle, Clemens Klöck, Karsten Heuschkel","doi":"10.1109/IECBES54088.2022.10079417","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079417","url":null,"abstract":"This work focused on vital sign monitoring of a sleeping subject in real-time using the AWR1642 Boost of Texas Instruments. A newly designed signal processing chain is proposed to obtain a clearly recognizable heart and breath signal from the raw radar data. The averaged breath and heart rates were then calculated from these breath and heart signals. For the evaluation of these frequencies, the pulse of the test person was measured parallel to the radar measurement with a Garmin Forerunner 735XT. The results of the research show, that it would be possible to implement a monitoring system with the help of a radar sensor.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124294757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079549
Pranav Bellannagari, Sohail Zaidi, V. Viswanathan
This paper provides a historical perspective on the design and development of mechatronically controlled assistive exoskeleton devices at San Jose State University (SJSU). The main design objective was to facilitate rehabilitative exercises for patients who have limited leg mobility and are required to conduct exercises without any external help. The paper starts by analyzing previous designs incorporating fluidic muscles that meet the requirements of running knee-related rehabilitation exercises. To activate the “Assistive Bionic Joint – ABJ” system, EMG sensors were mounted. Since a need for a bio-chair designed for partially paralyzed patients where EMG sensors can not be placed on the patient’s leg to generate a trigger signal for the system exists, this research serves as a solution. In this paper, the design of the bio-chair is thoroughly discussed, and the first assembled model was tested for its operation. This system is simple, economical, and user-friendly. It is anticipated to have further implications for the enrichment of muscle rehabilitation, such as higher patient morale, more muscle activity, and shortened recovery times.
{"title":"Design of a Biochair to Facilitate Leg Muscles Rehabilitation","authors":"Pranav Bellannagari, Sohail Zaidi, V. Viswanathan","doi":"10.1109/IECBES54088.2022.10079549","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079549","url":null,"abstract":"This paper provides a historical perspective on the design and development of mechatronically controlled assistive exoskeleton devices at San Jose State University (SJSU). The main design objective was to facilitate rehabilitative exercises for patients who have limited leg mobility and are required to conduct exercises without any external help. The paper starts by analyzing previous designs incorporating fluidic muscles that meet the requirements of running knee-related rehabilitation exercises. To activate the “Assistive Bionic Joint – ABJ” system, EMG sensors were mounted. Since a need for a bio-chair designed for partially paralyzed patients where EMG sensors can not be placed on the patient’s leg to generate a trigger signal for the system exists, this research serves as a solution. In this paper, the design of the bio-chair is thoroughly discussed, and the first assembled model was tested for its operation. This system is simple, economical, and user-friendly. It is anticipated to have further implications for the enrichment of muscle rehabilitation, such as higher patient morale, more muscle activity, and shortened recovery times.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121286395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079523
L. Chow, Ying Ze Soon, Yih Bing Chu, M. Paley, S. Hickman
This study aims to investigate the presence of evoked action potentials in the human optic nerve using magnetic resonance imaging (MRI). The detection method is based on the effect of the evoked action potentials, which produce the axonal current flowing through the optic nerve. It produces a minute axonal magnetic field around the optic nerve. The axonal current is expected to be generated at the same frequency as the evoked action potentials, which are at the same frequency as the visual stimulus during imaging. This study attempted to detect the axonal magnetic field variation which interacts with the MR main magnetic field, B0, and produces signal modulation during image acquisition. Consequently, there will be intra-voxel dephasing within the region of interest (ROI) in the optic nerve. The signal variation can be found by converting the time series signal into the frequency domain using a fast Fourier transform (FFT). The checkerboard visual stimulus was projected to the subject in synchronization with MRI using a gradient echo – echo planar imaging (GE-EPI) sequence. A total of five healthy volunteers and five optic neuritis patients were recruited for this study. The visual stimulus response was only found in one out of the five healthy volunteers, with an estimated axonal field of 7 nT. No response was found in the optic neuritis patients as expected due to the effects of the disease on optic nerve signaling. Clinical Relevance – This study measured the evoked action potentials in the optic nerve which will allow further study into the effects of optic neuritis on optic nerve signaling.
{"title":"Investigating Evoked Action Potential in Human Optic Nerves using MRI","authors":"L. Chow, Ying Ze Soon, Yih Bing Chu, M. Paley, S. Hickman","doi":"10.1109/IECBES54088.2022.10079523","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079523","url":null,"abstract":"This study aims to investigate the presence of evoked action potentials in the human optic nerve using magnetic resonance imaging (MRI). The detection method is based on the effect of the evoked action potentials, which produce the axonal current flowing through the optic nerve. It produces a minute axonal magnetic field around the optic nerve. The axonal current is expected to be generated at the same frequency as the evoked action potentials, which are at the same frequency as the visual stimulus during imaging. This study attempted to detect the axonal magnetic field variation which interacts with the MR main magnetic field, B0, and produces signal modulation during image acquisition. Consequently, there will be intra-voxel dephasing within the region of interest (ROI) in the optic nerve. The signal variation can be found by converting the time series signal into the frequency domain using a fast Fourier transform (FFT). The checkerboard visual stimulus was projected to the subject in synchronization with MRI using a gradient echo – echo planar imaging (GE-EPI) sequence. A total of five healthy volunteers and five optic neuritis patients were recruited for this study. The visual stimulus response was only found in one out of the five healthy volunteers, with an estimated axonal field of 7 nT. No response was found in the optic neuritis patients as expected due to the effects of the disease on optic nerve signaling. Clinical Relevance – This study measured the evoked action potentials in the optic nerve which will allow further study into the effects of optic neuritis on optic nerve signaling.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122505160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-07DOI: 10.1109/IECBES54088.2022.10079693
N. H. Khan, S. Joy, F. K. Che Harun, W. Chan, N. A. Abdul-Kadir, K. K. Moey
Wearable electrocardiogram (ECG) systems have increasingly been used in everyday life, breaking down the barriers that formerly existed only within hospitals. They allow for non-invasive continuous monitoring of a variety of heart parameters. The aim of this work is to investigate and assess the development of a user-friendly, mobile, and compact wearable ECG system for instantaneous recording. The work also presented the design of the ECG system with Autodesk EAGLE and Fusion 360 that has wireless connectivity via Bluetooth and Wi-Fi. The functionality of this ECG system is aided by the BMD101 cardio chip device, which is composed of an amplifier, filter, and 16-bit analog to digital converter. The results indicated the regular cardiac rhythm of 60 beats per minute (bpm), 120 bpm, and 180 bpm, respectively, along with the abnormal heart condition of ventricular tachycardia. Eventually, this study concluded with a list of key remaining obstacles as well as potential for development in terms of result display and system software, both of which are vital for continued advancement.
{"title":"Performance of A Wireless Electrocardiogram System based on Wi-Fi and BLE Technology","authors":"N. H. Khan, S. Joy, F. K. Che Harun, W. Chan, N. A. Abdul-Kadir, K. K. Moey","doi":"10.1109/IECBES54088.2022.10079693","DOIUrl":"https://doi.org/10.1109/IECBES54088.2022.10079693","url":null,"abstract":"Wearable electrocardiogram (ECG) systems have increasingly been used in everyday life, breaking down the barriers that formerly existed only within hospitals. They allow for non-invasive continuous monitoring of a variety of heart parameters. The aim of this work is to investigate and assess the development of a user-friendly, mobile, and compact wearable ECG system for instantaneous recording. The work also presented the design of the ECG system with Autodesk EAGLE and Fusion 360 that has wireless connectivity via Bluetooth and Wi-Fi. The functionality of this ECG system is aided by the BMD101 cardio chip device, which is composed of an amplifier, filter, and 16-bit analog to digital converter. The results indicated the regular cardiac rhythm of 60 beats per minute (bpm), 120 bpm, and 180 bpm, respectively, along with the abnormal heart condition of ventricular tachycardia. Eventually, this study concluded with a list of key remaining obstacles as well as potential for development in terms of result display and system software, both of which are vital for continued advancement.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125212351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：