Pub Date : 2024-11-08DOI: 10.1109/OJEMB.2024.3387895
{"title":"IEEE Open Journal of Engineering in Medicine and Biology Editorial Board Information","authors":"","doi":"10.1109/OJEMB.2024.3387895","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3387895","url":null,"abstract":"","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"C4-C4"},"PeriodicalIF":2.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10747779","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-07DOI: 10.1109/OJEMB.2024.3486457
Riccardo Barbieri;Maximiliano Mollura
{"title":"Guest Editorial: Introduction to the Special Series on Advances in Cardiovascular and Respiratory Systems Engineering","authors":"Riccardo Barbieri;Maximiliano Mollura","doi":"10.1109/OJEMB.2024.3486457","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3486457","url":null,"abstract":"","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"5 ","pages":"803-805"},"PeriodicalIF":2.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10746532","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Goal: To detect Hypertrophic Cardiomyopathy (HCM) from multiple views of Echocardiogram (cardiac ultrasound) videos. Methods: we propose HCM-Echo-VAR-Ensemble , a novel framework that performs binary classification (HCM vs. no HCM) of echocardiogram videos directly using an ensemble of state-of-the-art deep VAR architectures models (SlowFast and I3D), and fuses their predictions using majority averaging ensembling. Results: HCM-Echo-VAR-Ensemble achieved state-of-the-art accuracy of 95.28%, an F1-Score of 95.20%, a specificity of 96.20%, a sensitivity of 93.97%, a PPV of 96.46%, an NPV of 94.17%, and an AUC of 98.42%, outperforming a comprehensive set of baselines including other ensembling approaches. Conclusions: Our proposed HCM-Echo-VAR-Ensemble framework demonstrates significant potential for improving the sensitivity and accuracy of HCM detection in clinical settings, particularly by ensembling the complementary strengths of the SlowFast and I3D deep VAR models. This approach can enhance diagnostic consistency and accuracy, enabling reliable HCM diagnoses even in low-resource environments.
{"title":"HCM-Echo-VAR-Ensemble: Deep Ensemble Fusion to Detect Hypertrophic Cardiomyopathy in Echocardiograms","authors":"Abdulsalam Almadani;Atifa Sarwar;Emmanuel Agu;Monica Ahluwalia;Jacques Kpodonu","doi":"10.1109/OJEMB.2024.3486541","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3486541","url":null,"abstract":"<italic>Goal:</i>\u0000 To detect Hypertrophic Cardiomyopathy (HCM) from multiple views of Echocardiogram (cardiac ultrasound) videos. \u0000<italic>Methods:</i>\u0000 we propose \u0000<italic>HCM-Echo-VAR-Ensemble</i>\u0000, a novel framework that performs binary classification (HCM vs. no HCM) of echocardiogram videos directly using an ensemble of state-of-the-art deep VAR architectures models (SlowFast and I3D), and fuses their predictions using majority averaging ensembling. \u0000<italic>Results:</i>\u0000 \u0000<italic>HCM-Echo-VAR-Ensemble</i>\u0000 achieved state-of-the-art accuracy of 95.28%, an F1-Score of 95.20%, a specificity of 96.20%, a sensitivity of 93.97%, a PPV of 96.46%, an NPV of 94.17%, and an AUC of 98.42%, outperforming a comprehensive set of baselines including other ensembling approaches. \u0000<italic>Conclusions:</i>\u0000 Our proposed HCM-Echo-VAR-Ensemble framework demonstrates significant potential for improving the sensitivity and accuracy of HCM detection in clinical settings, particularly by ensembling the complementary strengths of the SlowFast and I3D deep VAR models. This approach can enhance diagnostic consistency and accuracy, enabling reliable HCM diagnoses even in low-resource environments.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"193-201"},"PeriodicalIF":2.7,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10735780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1109/OJEMB.2024.3485534
Shiau-Ru Yang;Jen-Tzung Chien;Chen-Yi Lee
Owing to the rapid progress in artificial intelligence (AI) and the widespread use of generative learning, the problem of sparse data has been solved effectively in various research fields. The application of AI technologies has resulted in important transformations in healthcare, particularly in radiology. To ensure the high quality, safety, and effectiveness of AI and machine learning (ML) medical devices, the US Food and Drug Administration (FDA) has established regulatory guidelines to support the performance evaluation of medical devices. Furthermore, the FDA has proposed continuous surveillance requirements for AI/ML medical devices. This paper presents a summary of SaMD products that have passed the FDA 510 (k) AI/ML pathway, the challenges associated with the current AI/ML software-as-a-medical-device, and solutions for promoting the development of AI technologies in medicine. We hope to provide valuable information pertaining to medical-device design, development, and monitoring to ultimately achieve safer and more effective personalized medical services.
{"title":"Advancements in Clinical Evaluation and Regulatory Frameworks for AI-Driven Software as a Medical Device (SaMD)","authors":"Shiau-Ru Yang;Jen-Tzung Chien;Chen-Yi Lee","doi":"10.1109/OJEMB.2024.3485534","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3485534","url":null,"abstract":"Owing to the rapid progress in artificial intelligence (AI) and the widespread use of generative learning, the problem of sparse data has been solved effectively in various research fields. The application of AI technologies has resulted in important transformations in healthcare, particularly in radiology. To ensure the high quality, safety, and effectiveness of AI and machine learning (ML) medical devices, the US Food and Drug Administration (FDA) has established regulatory guidelines to support the performance evaluation of medical devices. Furthermore, the FDA has proposed continuous surveillance requirements for AI/ML medical devices. This paper presents a summary of SaMD products that have passed the FDA 510 (k) AI/ML pathway, the challenges associated with the current AI/ML software-as-a-medical-device, and solutions for promoting the development of AI technologies in medicine. We hope to provide valuable information pertaining to medical-device design, development, and monitoring to ultimately achieve safer and more effective personalized medical services.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"147-151"},"PeriodicalIF":2.7,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10729844","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1109/OJEMB.2024.3485535
James Skoric;Yannick D'Mello;David V. Plant
Goal: Seismocardiography (SCG) offers critical insights into cardiac performance, but its analysis often faces challenges due to the limited availability of data. This study aims to generate synthetic SCG heartbeats which can augment existing datasets to enable more research avenues. Methods : We trained a Wasserstein generative adversarial network (GAN) with gradient penalty on authentic SCG heartbeats. It was conditioned with embedded subject-specific identifiers to create individualized heartbeats. We employed linear permutations in the latent and conditional spaces to control signal features, and a convolutional network to classify lung volume states from real and synthetic data separately. Results : The model effectively replicated SCG signal morphology, while maintaining a level of variance which matches the variability of cardiac activity. Comparisons with real SCG waveforms yielded Pearson's r-squared correlation of 0.62 for average heartbeats. Linear manipulations were successful in controlling simple features although they were limited in more complex characteristics. Additionally, the model demonstrated strong performance in practical applications, with the synthetic data achieving an accuracy of 88% in lung volume classification as compared to 89% achieved with real data. Augmenting real data with additional synthetic data improved performance by 3%. Conclusions : GANs for artificial SCG heartbeat generation produce realistic and diverse results that have the potential to overcome data limitations, thereby enhancing SCG-based research.
{"title":"Generation of Seismocardiography Heartbeats Using a Wasserstein Generative Adversarial Network With Feature Control","authors":"James Skoric;Yannick D'Mello;David V. Plant","doi":"10.1109/OJEMB.2024.3485535","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3485535","url":null,"abstract":"<italic>Goal:</i>\u0000 Seismocardiography (SCG) offers critical insights into cardiac performance, but its analysis often faces challenges due to the limited availability of data. This study aims to generate synthetic SCG heartbeats which can augment existing datasets to enable more research avenues. \u0000<italic>Methods</i>\u0000: We trained a Wasserstein generative adversarial network (GAN) with gradient penalty on authentic SCG heartbeats. It was conditioned with embedded subject-specific identifiers to create individualized heartbeats. We employed linear permutations in the latent and conditional spaces to control signal features, and a convolutional network to classify lung volume states from real and synthetic data separately. \u0000<italic>Results</i>\u0000: The model effectively replicated SCG signal morphology, while maintaining a level of variance which matches the variability of cardiac activity. Comparisons with real SCG waveforms yielded Pearson's r-squared correlation of 0.62 for average heartbeats. Linear manipulations were successful in controlling simple features although they were limited in more complex characteristics. Additionally, the model demonstrated strong performance in practical applications, with the synthetic data achieving an accuracy of 88% in lung volume classification as compared to 89% achieved with real data. Augmenting real data with additional synthetic data improved performance by 3%. \u0000<italic>Conclusions</i>\u0000: GANs for artificial SCG heartbeat generation produce realistic and diverse results that have the potential to overcome data limitations, thereby enhancing SCG-based research.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"119-126"},"PeriodicalIF":2.7,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10731564","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1109/OJEMB.2024.3482878
Ramon Rohner;David E. Bauer;Martin Hartmann;Tobias Götschi;Mazda Farshad;Jonas Widmer
Introduction: Pedicle screw loosening is a major problem in spine surgery. Computed tomography (CT) is the gold standard to diagnose screw loosening. Disadvantages of CT include low sensitivity and specificity for the detection of loosened screws as well as the need for radiation exposure. The aim of this study was to provide a proof of concept of a novel, non-invasive, inductive sensing device for transcutaneous detection of screw loosening using a pulse induction metal detector. Materials/Methods: Two fresh frozen human cadavers were initially instrumented in the lumbar spinal region (L1 to L5). After assessment of the sensing device behavior using a wooden beam and 3D printed place holders of predefined distances, the ability of implant detection and screw stability determination were assessed during two experiments. Pedicle screw loosening was induced using 3D printed drill/loosening guides during the instrumentation of the lumbar spine. Screw stability was determined by applying weight to the spinous processes of interest and measuring the relative movement of the pedicle screw using the inductive sensor coil. Results: The sensitivity of our detection coil for an implant movement measurement showed to be high at close distances (60mV voltage change per mm movement), with signal amplitude vanishing at sensing distances of 50mm or greater. Signal amplitude significantly (p < .05) differed with the number of instrumented levels. When differentiating between instrumentation with and without loosened screws, significant (p < .05) mean differences were found in half of all comparative cases. All these differences were smaller than the predefined signal voltage threshold of (60 mV/mm). Discussion/Conclusion: In this study, the feasibility of a new, inductive and non-invasive sensor concept was tested. While the basic principle of the approach is promising, our implementation was not successful in demonstrating sufficient sensitivity for the required detectability. It appears conceivable that the concept can be successfully implemented with more sensitive sensors and more complex evaluation methods.
{"title":"Feasibility of an Inductive Pedicle Screw Loosening Detection Concept Using a Pulse Induction Metal Detector","authors":"Ramon Rohner;David E. Bauer;Martin Hartmann;Tobias Götschi;Mazda Farshad;Jonas Widmer","doi":"10.1109/OJEMB.2024.3482878","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3482878","url":null,"abstract":"<italic>Introduction:</i>\u0000 Pedicle screw loosening is a major problem in spine surgery. Computed tomography (CT) is the gold standard to diagnose screw loosening. Disadvantages of CT include low sensitivity and specificity for the detection of loosened screws as well as the need for radiation exposure. The aim of this study was to provide a proof of concept of a novel, non-invasive, inductive sensing device for transcutaneous detection of screw loosening using a pulse induction metal detector. \u0000<italic>Materials/Methods:</i>\u0000 Two fresh frozen human cadavers were initially instrumented in the lumbar spinal region (L1 to L5). After assessment of the sensing device behavior using a wooden beam and 3D printed place holders of predefined distances, the ability of implant detection and screw stability determination were assessed during two experiments. Pedicle screw loosening was induced using 3D printed drill/loosening guides during the instrumentation of the lumbar spine. Screw stability was determined by applying weight to the spinous processes of interest and measuring the relative movement of the pedicle screw using the inductive sensor coil. \u0000<italic>Results:</i>\u0000 The sensitivity of our detection coil for an implant movement measurement showed to be high at close distances (60mV voltage change per mm movement), with signal amplitude vanishing at sensing distances of 50mm or greater. Signal amplitude significantly (p < .05) differed with the number of instrumented levels. When differentiating between instrumentation with and without loosened screws, significant (p < .05) mean differences were found in half of all comparative cases. All these differences were smaller than the predefined signal voltage threshold of (60 mV/mm). \u0000<italic>Discussion/Conclusion:</i>\u0000 In this study, the feasibility of a new, inductive and non-invasive sensor concept was tested. While the basic principle of the approach is promising, our implementation was not successful in demonstrating sufficient sensitivity for the required detectability. It appears conceivable that the concept can be successfully implemented with more sensitive sensors and more complex evaluation methods.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"113-118"},"PeriodicalIF":2.7,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720821","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1109/OJEMB.2024.3480708
Mohammed Aburidi;Roummel Marcia
Objective: The development of pharmaceutical agents relies heavily on optimizing their pharmacodynamics, pharmacokinetics, and toxicological properties, collectively known as ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity). Accurate assessment of these properties during the early stages of drug development is challenging due to resource-intensive experimental evaluation and limited comprehensive data availability. To overcome these obstacles, there has been a growing reliance on computational and predictive tools, leveraging recent advancements in machine learning and graph-based methodologies. This study presents an innovative approach that harnesses the power of optimal transport (OT) theory to construct three graph kernels for predicting drug ADMET properties. This approach involves the use of graph matching to create a similarity matrix, which is subsequently integrated into a predictive model. Results: Through extensive evaluations on 19 distinct ADMET datasets, the potential of this methodology becomes evident. The OT-based graph kernels exhibits exceptional performance, outperforming state-of-the-art graph deep learning models in 9 out of 19 datasets, even surpassing the most impactful Graph Neural Network (GNN) that excels in 4 datasets. Furthermore, they are very competitive in 2 additional datasets. Conclusion: Our proposed novel class of OT-based graph kernels not only demonstrates a high degree of effectiveness and competitiveness but also, in contrast to graph neural networks, offers interpretability, adaptability and generalizability across multiple datasets.
{"title":"Optimal Transport Based Graph Kernels for Drug Property Prediction","authors":"Mohammed Aburidi;Roummel Marcia","doi":"10.1109/OJEMB.2024.3480708","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3480708","url":null,"abstract":"<italic>Objective:</i>\u0000 The development of pharmaceutical agents relies heavily on optimizing their pharmacodynamics, pharmacokinetics, and toxicological properties, collectively known as ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity). Accurate assessment of these properties during the early stages of drug development is challenging due to resource-intensive experimental evaluation and limited comprehensive data availability. To overcome these obstacles, there has been a growing reliance on computational and predictive tools, leveraging recent advancements in machine learning and graph-based methodologies. This study presents an innovative approach that harnesses the power of optimal transport (OT) theory to construct three graph kernels for predicting drug ADMET properties. This approach involves the use of graph matching to create a similarity matrix, which is subsequently integrated into a predictive model. \u0000<italic>Results:</i>\u0000 Through extensive evaluations on 19 distinct ADMET datasets, the potential of this methodology becomes evident. The OT-based graph kernels exhibits exceptional performance, outperforming state-of-the-art graph deep learning models in 9 out of 19 datasets, even surpassing the most impactful Graph Neural Network (GNN) that excels in 4 datasets. Furthermore, they are very competitive in 2 additional datasets. \u0000<italic>Conclusion:</i>\u0000 Our proposed novel class of OT-based graph kernels not only demonstrates a high degree of effectiveness and competitiveness but also, in contrast to graph neural networks, offers interpretability, adaptability and generalizability across multiple datasets.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"152-157"},"PeriodicalIF":2.7,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10716457","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Goal: Organ perfusion is a vast subject with several techniques, the most common being Hypothermic Machine Perfusion (HMP) and Normothermic Machine Perfusion (NMP). In this paper, a new machine developed at the Biolab of the University of Florence has been tested to validate its capability to perform a well-controlled Oxygenated Rewarming (COR) phase and maintain stability during the NMP phase. Methods: The tests (n = 5) were conducted on fresh porcine livers and evaluated according to liver perfusion standards. The developed machine is based on a previous version, with an integrated control and sensor system and a complete mechanical and electronic redesign. Results: The results demonstrate the excellent usability of the machine and its ability to effectively maintain the organs in good condition. The new system performed well, and the measures made on the livers were satisfactory for good preservation of the organ. Conclusion: This study showed the effectiveness of the developed machine. Future development of the system will include a more sophisticated control system to ensure the correct parameters for perfusion.
{"title":"Experimental Evaluation of a New Perfusion Machine Using Normothermic Cycles on Explanted Livers","authors":"Eleonora Barcali;Lorenzo Maggi;Rebecca Panconesi;Fabio Staderini;Leonardo Bocchi;Cosimo Nardi;Nadia Navari;Adriano Peris;Matteo Risaliti;Mauricio F. Carvalho;Fabio Marra;Philipp Dutkowski;Gian Luca Grazi;Andrea Schlegel;Filippo Bigi;Mattia Dimitri;Andrea Corvi","doi":"10.1109/OJEMB.2024.3478791","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3478791","url":null,"abstract":"<italic>Goal:</i>\u0000 Organ perfusion is a vast subject with several techniques, the most common being Hypothermic Machine Perfusion (HMP) and Normothermic Machine Perfusion (NMP). In this paper, a new machine developed at the Biolab of the University of Florence has been tested to validate its capability to perform a well-controlled Oxygenated Rewarming (COR) phase and maintain stability during the NMP phase. \u0000<italic>Methods:</i>\u0000 The tests (n = 5) were conducted on fresh porcine livers and evaluated according to liver perfusion standards. The developed machine is based on a previous version, with an integrated control and sensor system and a complete mechanical and electronic redesign. \u0000<italic>Results:</i>\u0000 The results demonstrate the excellent usability of the machine and its ability to effectively maintain the organs in good condition. The new system performed well, and the measures made on the livers were satisfactory for good preservation of the organ. \u0000<italic>Conclusion:</i>\u0000 This study showed the effectiveness of the developed machine. Future development of the system will include a more sophisticated control system to ensure the correct parameters for perfusion.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"82-88"},"PeriodicalIF":2.7,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10713905","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: Acute electrical stimulation of the common peroneal nerve (cPNS) has been shown to cause an immediate reduction in systolic blood pressure (SBP) in spontaneous hypertense rats (SHR), but the effect of this treatment in sub-chronic ambulatory SBP is unknown. Here we developed an implantable wireless WNClip neural stimulator to test the efficacy of 5-week cPNS as a treatment for hypertension. Results: Daily cPNS 2 Hz monophasic stimulation at threshold for 8 minutes every day for five weeks, reduced SBP in WKY animals by −4 mm Hg, and in SHR animals by −21 mmHg in week 5 (p < 0.01). Ambulatory SBP measured daily recorded approximately twenty-four hours after the cPNS treatment, showed a significant reduction from the first (176.6 ± 24.1 mm Hg; n = 5) to the last week of treatment (165.7± 42.7 mm Hg; n = 4), a −9 mm Hg reduction (p < 0.01). Evaluation of heart rate during the treatment showed no significant difference caused by the daily 8-minute cPNS. Conclusions: Electrical stimulation of the common peroneal nerve induced a reduction in SBP that is comparable to that reportedly achieved pharmacologically by ACE inhibitor Ramipril, or by renal denervation procedures. These results support the notion that neuromodulation of the common peroneal nerve can serve as an alternative treatment for drug resistant hypertension.
{"title":"Sub-Chronic Peroneal Nerve Stimulation Lowers Ambulatory Blood Pressure in Spontaneously Hypertensive Rats","authors":"K. Romero;M.A. Gonzalez-Gonzalez;D. Lloyd;K. Nguyen;N. Eli;Y. Akay;W. Vongpatanasin;S. Smith;M. Akay;MI Romero-Ortega","doi":"10.1109/OJEMB.2024.3477411","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3477411","url":null,"abstract":"<italic>Objective:</i>\u0000 Acute electrical stimulation of the common peroneal nerve (cPNS) has been shown to cause an immediate reduction in systolic blood pressure (SBP) in spontaneous hypertense rats (SHR), but the effect of this treatment in sub-chronic ambulatory SBP is unknown. Here we developed an implantable wireless WNClip neural stimulator to test the efficacy of 5-week cPNS as a treatment for hypertension. \u0000<italic>Results:</i>\u0000 Daily cPNS 2 Hz monophasic stimulation at threshold for 8 minutes every day for five weeks, reduced SBP in WKY animals by −4 mm Hg, and in SHR animals by −21 mmHg in week 5 (p < 0.01). Ambulatory SBP measured daily recorded approximately twenty-four hours after the cPNS treatment, showed a significant reduction from the first (176.6 ± 24.1 mm Hg; n = 5) to the last week of treatment (165.7± 42.7 mm Hg; n = 4), a −9 mm Hg reduction (p < 0.01). Evaluation of heart rate during the treatment showed no significant difference caused by the daily 8-minute cPNS. \u0000<italic>Conclusions:</i>\u0000 Electrical stimulation of the common peroneal nerve induced a reduction in SBP that is comparable to that reportedly achieved pharmacologically by ACE inhibitor Ramipril, or by renal denervation procedures. These results support the notion that neuromodulation of the common peroneal nerve can serve as an alternative treatment for drug resistant hypertension.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"140-146"},"PeriodicalIF":2.7,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10713865","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1109/OJEMB.2024.3477267
Patrick Kiele;Gregor Laengle;Martin Schmoll;Cristian Pasluosta;Ronny Pfeifer;Martin Schuettler;Oskar Aszmann;Thomas Stieglitz
Goal: Transcutaneous coupling scheme for wireless powering and signal in active implants are known for more than a decade. This study aimed to investigate the in vivo behavior of this approach to drive multiple channels of an implanted peripheral nerve interfaces. Methods: The stimulation signals were transmitted through the skin over two contacts to an intracorporeal counterpart which was connected to a cuff electrode with two channels. EMG after stimulation was measured to establish recruitment curves. Results: Limitations of transcutaneous coupling were found in the feasible complexity of the system. High electrical crosstalk in a multi-channel system reduces this approach to low channel applications, such as pain treatment. No significant influence of the pulse width or extracorporeal stimulation amplitude on the electrical crosstalk was observed. Conclusions: The study's findings provide insight into the behavior of the transcutaneous coupling scheme in vivo and highlight the limitations and areas of application. Our results indicate that transcutaneous coupling schemes are a promising alternative approach for wireless powering of implants, as it does not require complex implanted electronics, expensive sophisticated electronics, and hermetic enclosures. Physical constraints, however, limit the use in highly selective nerve stimulation scenarios.
{"title":"Neural Implants Without Active Implanted Electronics: Possibilities and Limitations of Transcutaneous Coupling in Miniaturized Active Implants","authors":"Patrick Kiele;Gregor Laengle;Martin Schmoll;Cristian Pasluosta;Ronny Pfeifer;Martin Schuettler;Oskar Aszmann;Thomas Stieglitz","doi":"10.1109/OJEMB.2024.3477267","DOIUrl":"https://doi.org/10.1109/OJEMB.2024.3477267","url":null,"abstract":"<italic>Goal:</i>\u0000 Transcutaneous coupling scheme for wireless powering and signal in active implants are known for more than a decade. This study aimed to investigate the in vivo behavior of this approach to drive multiple channels of an implanted peripheral nerve interfaces. \u0000<italic>Methods:</i>\u0000 The stimulation signals were transmitted through the skin over two contacts to an intracorporeal counterpart which was connected to a cuff electrode with two channels. EMG after stimulation was measured to establish recruitment curves. \u0000<italic>Results:</i>\u0000 Limitations of transcutaneous coupling were found in the feasible complexity of the system. High electrical crosstalk in a multi-channel system reduces this approach to low channel applications, such as pain treatment. No significant influence of the pulse width or extracorporeal stimulation amplitude on the electrical crosstalk was observed. \u0000<italic>Conclusions:</i>\u0000 The study's findings provide insight into the behavior of the transcutaneous coupling scheme in vivo and highlight the limitations and areas of application. Our results indicate that transcutaneous coupling schemes are a promising alternative approach for wireless powering of implants, as it does not require complex implanted electronics, expensive sophisticated electronics, and hermetic enclosures. Physical constraints, however, limit the use in highly selective nerve stimulation scenarios.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"6 ","pages":"69-74"},"PeriodicalIF":2.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10710177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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