Pub Date : 2026-01-29DOI: 10.1109/JTEHM.2026.3659415
{"title":"2025 Index IEEE Journal of Translational Engineering in Health and Medicine Vol. 13","authors":"","doi":"10.1109/JTEHM.2026.3659415","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3659415","url":null,"abstract":"","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"13 ","pages":"573-588"},"PeriodicalIF":4.4,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11368643","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: In the psychology community, there is currently no standardized framework for assessing body schema distortions, either in research or clinical practice. To address this gap, we propose RECORD (RECOnfiguRing the Assessment of the boDy in motion), a cost-effective clinical tool designed to assess shoulder rotation as patient walks towards doorways. Methods and procedures: RECORD utilizes a single wireless pod, featuring an inertial measurement unit (IMU), placed on the acromion, which is adequate for measuring shoulder rotation. Our approach uses quaternion-based algorithm for robustness. We provide a comparison with gold-standard motion capture system, along with performance metrics and benchmark testing. Results: The system has demonstrated a constant accuracy of 1.39° within the task range, regardless of the distance or movement performed by the subject. Conclusion: The device is adapted for assessing shoulder rotation in clinical practice and in psychological research contexts. The source files of the RECORD device hardware, algorithms and software codes are available on the open-source GitHub RECORD repository to enable accessibility, as well as future contributions to benefit the community.
{"title":"RECORD: A Simple, Low-Cost, and Open-Source IMU-Based Tool for the Diagnosis of Body Schema Distortions","authors":"Luc Marechal;Christian Elmo Kulanesan;Louise Dupraz;Morgane Metral;Jessica Bourgin;Blaise Girard","doi":"10.1109/JTEHM.2026.3655633","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3655633","url":null,"abstract":"Objective: In the psychology community, there is currently no standardized framework for assessing body schema distortions, either in research or clinical practice. To address this gap, we propose RECORD (RECOnfiguRing the Assessment of the boDy in motion), a cost-effective clinical tool designed to assess shoulder rotation as patient walks towards doorways. Methods and procedures: RECORD utilizes a single wireless pod, featuring an inertial measurement unit (IMU), placed on the acromion, which is adequate for measuring shoulder rotation. Our approach uses quaternion-based algorithm for robustness. We provide a comparison with gold-standard motion capture system, along with performance metrics and benchmark testing. Results: The system has demonstrated a constant accuracy of 1.39° within the task range, regardless of the distance or movement performed by the subject. Conclusion: The device is adapted for assessing shoulder rotation in clinical practice and in psychological research contexts. The source files of the RECORD device hardware, algorithms and software codes are available on the open-source GitHub RECORD repository to enable accessibility, as well as future contributions to benefit the community.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"45-54"},"PeriodicalIF":4.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11358976","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/JTEHM.2026.3653176
A. Gobbi;C. Gulotta;B. Suki;E. Mellano;M. Vitacca;F. Colombo;V. Brusasco;C. Veneroni;R. Dellacà
Objective: Assessment of lung function variability is recommended for the diagnosis of asthma, but its specificity in separating asthmatic from COPD subjects is low. This study aimed to test the hypothesis that the day-to-day variability of respiratory resistance depends on the respiratory phase considered and observation time. Methods: Respiratory resistance was measured daily by oscillometry at 5 Hz in 47 mild asthmatics, 20 moderate-to-severe COPD, and 35 healthy subjects. The coefficient of variation was calculated over multiple time scales using full breaths, inspiratory phase, or mid-inspiratory phase. Results: The coefficient of variation of mid-inspiratory resistance was significantly higher in asthmatic than healthy and COPD groups at time scales >7 days, but not different between healthy and COPD. The accuracy of the 14-days coefficient of variation of mid-inspiratory resistance in separating asthmatic from the other groups, calculated as the area under the receiver-operating characteristic curve, was 0.86, with 73% sensitivity and 83% specificity at the optimal cutoff of 10%. Moreover, the coefficient of variation was significantly higher in asthma than COPD despite an increased mean resistance in the latter. Conclusion: When expressed as the day-to-day coefficient of variation of mid-inspiratory oscillometric resistance, the variability of lung function does not appear related to the presence or degree of airflow obstruction. Two-week assessment of day-to-day variability of mid-inspiratory resistance provides accurate separation of asthmatic from both healthy and COPD subjects. These findings demonstrate that simple, self-administered daily oscillometry can provide useful clinical information, supporting more accurate asthma diagnosis in real-world settings. Clinical and Translational Impact—The coefficient of variation of mid-inspiratory resistance computed over 14-days separated asthmatic from healthy and COPD subjects with 73% sensitivity and 83% specificity. Daily self-administered oscillometry can support asthma diagnosis.
{"title":"Day-to-Day Variability of Respiratory Resistance in Asthma and COPD: Influence of Intra-Breath Data Sampling and Observation Period","authors":"A. Gobbi;C. Gulotta;B. Suki;E. Mellano;M. Vitacca;F. Colombo;V. Brusasco;C. Veneroni;R. Dellacà","doi":"10.1109/JTEHM.2026.3653176","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3653176","url":null,"abstract":"Objective: Assessment of lung function variability is recommended for the diagnosis of asthma, but its specificity in separating asthmatic from COPD subjects is low. This study aimed to test the hypothesis that the day-to-day variability of respiratory resistance depends on the respiratory phase considered and observation time. Methods: Respiratory resistance was measured daily by oscillometry at 5 Hz in 47 mild asthmatics, 20 moderate-to-severe COPD, and 35 healthy subjects. The coefficient of variation was calculated over multiple time scales using full breaths, inspiratory phase, or mid-inspiratory phase. Results: The coefficient of variation of mid-inspiratory resistance was significantly higher in asthmatic than healthy and COPD groups at time scales >7 days, but not different between healthy and COPD. The accuracy of the 14-days coefficient of variation of mid-inspiratory resistance in separating asthmatic from the other groups, calculated as the area under the receiver-operating characteristic curve, was 0.86, with 73% sensitivity and 83% specificity at the optimal cutoff of 10%. Moreover, the coefficient of variation was significantly higher in asthma than COPD despite an increased mean resistance in the latter. Conclusion: When expressed as the day-to-day coefficient of variation of mid-inspiratory oscillometric resistance, the variability of lung function does not appear related to the presence or degree of airflow obstruction. Two-week assessment of day-to-day variability of mid-inspiratory resistance provides accurate separation of asthmatic from both healthy and COPD subjects. These findings demonstrate that simple, self-administered daily oscillometry can provide useful clinical information, supporting more accurate asthma diagnosis in real-world settings. Clinical and Translational Impact—The coefficient of variation of mid-inspiratory resistance computed over 14-days separated asthmatic from healthy and COPD subjects with 73% sensitivity and 83% specificity. Daily self-administered oscillometry can support asthma diagnosis.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"29-35"},"PeriodicalIF":4.4,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11346541","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/JTEHM.2026.3653633
Osama Elgabori;William B. Scammon;Kelly R. Strong;Jingyi Wu;Keith E. Cook;Jana M. Kainerstorfer
Objective: Whole blood oxygen saturation and hemoglobin concentration are key markers of health across a variety of clinical contexts. Extracorporeal systems (dialysis, cardiopulmonary bypass, ECMO, etc.) require close monitoring of these parameters for proper patient treatment and intervention. Currently, blood gas analyzers are the gold standard for such measurements, however, these devices are invasive and fail to provide real-time results. In contrast, optical sensors can non-invasively probe whole blood for real-time monitoring of oxygen saturation and hemoglobin concentration. While commercial devices that implement such sensors exist, they not only fail to reduce the overall footprint of extracorporeal systems but instead increase it. Technology or Method: In this work, we develop small form factor optical sensors to be compatible with extracorporeal systems and obtain accurate real-time results using an empirical calibration method. We evaluate the performance of a pair of these optical sensors using this calibration through in-vitro experiments with whole blood. Results: Results showed an average accuracy root-mean square error of 1.30 g/dL for hemoglobin concentration and 4.76 % for saturation. Conclusions: These results demonstrate the potential viability of these sensors for use in assessing extracorporeal device performance and patient health.
{"title":"Development of an Optical Sensor for Real-Time Monitoring of Hemodynamic Parameters in Extracorporeal Settings","authors":"Osama Elgabori;William B. Scammon;Kelly R. Strong;Jingyi Wu;Keith E. Cook;Jana M. Kainerstorfer","doi":"10.1109/JTEHM.2026.3653633","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3653633","url":null,"abstract":"Objective: Whole blood oxygen saturation and hemoglobin concentration are key markers of health across a variety of clinical contexts. Extracorporeal systems (dialysis, cardiopulmonary bypass, ECMO, etc.) require close monitoring of these parameters for proper patient treatment and intervention. Currently, blood gas analyzers are the gold standard for such measurements, however, these devices are invasive and fail to provide real-time results. In contrast, optical sensors can non-invasively probe whole blood for real-time monitoring of oxygen saturation and hemoglobin concentration. While commercial devices that implement such sensors exist, they not only fail to reduce the overall footprint of extracorporeal systems but instead increase it. Technology or Method: In this work, we develop small form factor optical sensors to be compatible with extracorporeal systems and obtain accurate real-time results using an empirical calibration method. We evaluate the performance of a pair of these optical sensors using this calibration through in-vitro experiments with whole blood. Results: Results showed an average accuracy root-mean square error of 1.30 g/dL for hemoglobin concentration and 4.76 % for saturation. Conclusions: These results demonstrate the potential viability of these sensors for use in assessing extracorporeal device performance and patient health.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"36-44"},"PeriodicalIF":4.4,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11346963","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-25DOI: 10.1109/JTEHM.2025.3648704
Haakon Reithe;Monica Patrascu;Juan C. Torrado;Elise Førsund;Bettina S. Husebo;Simon U. Kverneng;Erika Sheard;Charalampos Tzoulis;Brice Marty
Objective: Tremor symptoms in Parkinson’s disease (PD) are challenging to assess due to low resolution and subjectivity from standard clinical scales. To address this, wearable devices have been used, but algorithms have been relying on controlled or limited activity conditions. Our objective is to create a context-independent metric quantifying tremor in free-living conditions to bridge the gap between biomedical engineering and the PD field. Methods and Procedures: We designed an algorithm which computes a tremor index (TI) from accelerometer data, collected via the Empatica E4 worn on the wrist by home dwelling people with PD. For validation, we use a within-participant design, comparing the TIs of the most and least tremor-affected hand. We included seven participants with unilateral tremor, monitored for two weeks each. The algorithm is able to compute TIs for a set of frequencies identified in literature as associated with different tremor types (3–12 Hz), over adjustable sampling time windows. Results: We show that the most tremor-affected hand yields a higher TI than the other hand for frequency sets that are individual to each person, in particular around 5-6 Hz where rest tremor typically occurs. We find that we can disambiguate tremor across 3-12 Hz from general movement and resting states. The number of frequencies with inter-hand separation correlate with the MDS-UPDRS part III tremor items. Conclusion: The designed tremor quantification algorithm can quantify tremor symptoms over time for people with PD and can be used to identify the individualized frequency ranges where these movements happen, in free-living conditions.
{"title":"Wavelet-Based Tremor Quantification From Wrist-Worn Sensor Data in Home-Dwelling People With Parkinson’s Disease","authors":"Haakon Reithe;Monica Patrascu;Juan C. Torrado;Elise Førsund;Bettina S. Husebo;Simon U. Kverneng;Erika Sheard;Charalampos Tzoulis;Brice Marty","doi":"10.1109/JTEHM.2025.3648704","DOIUrl":"https://doi.org/10.1109/JTEHM.2025.3648704","url":null,"abstract":"Objective: Tremor symptoms in Parkinson’s disease (PD) are challenging to assess due to low resolution and subjectivity from standard clinical scales. To address this, wearable devices have been used, but algorithms have been relying on controlled or limited activity conditions. Our objective is to create a context-independent metric quantifying tremor in free-living conditions to bridge the gap between biomedical engineering and the PD field. Methods and Procedures: We designed an algorithm which computes a tremor index (TI) from accelerometer data, collected via the Empatica E4 worn on the wrist by home dwelling people with PD. For validation, we use a within-participant design, comparing the TIs of the most and least tremor-affected hand. We included seven participants with unilateral tremor, monitored for two weeks each. The algorithm is able to compute TIs for a set of frequencies identified in literature as associated with different tremor types (3–12 Hz), over adjustable sampling time windows. Results: We show that the most tremor-affected hand yields a higher TI than the other hand for frequency sets that are individual to each person, in particular around 5-6 Hz where rest tremor typically occurs. We find that we can disambiguate tremor across 3-12 Hz from general movement and resting states. The number of frequencies with inter-hand separation correlate with the MDS-UPDRS part III tremor items. Conclusion: The designed tremor quantification algorithm can quantify tremor symptoms over time for people with PD and can be used to identify the individualized frequency ranges where these movements happen, in free-living conditions.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"19-28"},"PeriodicalIF":4.4,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11316150","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1109/JTEHM.2025.3636375
{"title":"List of Reviewers","authors":"","doi":"10.1109/JTEHM.2025.3636375","DOIUrl":"https://doi.org/10.1109/JTEHM.2025.3636375","url":null,"abstract":"","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"13 ","pages":"571-572"},"PeriodicalIF":4.4,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11313662","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-22DOI: 10.1109/JTEHM.2025.3636341
{"title":"IEEE Journal on Translational Engineering in Medicine and Biology publication information","authors":"","doi":"10.1109/JTEHM.2025.3636341","DOIUrl":"https://doi.org/10.1109/JTEHM.2025.3636341","url":null,"abstract":"","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"13 ","pages":"C3-C3"},"PeriodicalIF":4.4,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11311367","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-28DOI: 10.1109/JTEHM.2025.3638856
Jan-Willem Klok;Yannick Smits;Roelf Postema;Asþor T. Steinþorsson;Jenny Dankelman;Tim Horeman
Objective: Grasping force control is crucial for safe laparoscopic surgery. However, force feedback is limited as haptic information on grasping strength and tissue stiffness is mostly lost due to internal instrument backlash and friction. This increases tissue trauma risk as excessive grasping forces can lead to (postoperative) complications. This study aims to develop a grasping force feedback providing add-on for a laparoscopic grasper and to validate its impact on skills acquisition in basic laparoscopic skills training. Method: The ShaftFlex, a shaft-based grasping force measurement system providing feedback was designed as an add-on for standard reusable instruments. It consists of a compliant element deflecting proportionally to the applied grasping force, and a Hall sensor measuring that deflection. Influence on skills acquisition was evaluated in a comparative study where novices were divided into a Feedback and No feedback group, performing five training trials of a silicon torus transfer boxtrainer task. Afterwards, both groups performed a post-training task without feedback. Grasping force, time to completion and number of errors were measured. Results: There was a significant difference in mean grasping force between groups for all training trials and the post-training trial. In the Feedback group, there was no significant increase in grasping force when feedback was removed. Conclusion: The ShaftFlex working principle provided a feasible, sustainable method to measure grasping forces exerted by a laparoscopic grasper, enabling immediate haptic feedback. It potentially enhances objective skill assessment, providing feedback on training performance. In a clinical context, the ShaftFlex might be useful in surgery where delicate tissue is grasped.
{"title":"Design and Validation of a Grasping Force Measuring Vibrotactile Feedback Add-On for Laparoscopic Instruments","authors":"Jan-Willem Klok;Yannick Smits;Roelf Postema;Asþor T. Steinþorsson;Jenny Dankelman;Tim Horeman","doi":"10.1109/JTEHM.2025.3638856","DOIUrl":"https://doi.org/10.1109/JTEHM.2025.3638856","url":null,"abstract":"Objective: Grasping force control is crucial for safe laparoscopic surgery. However, force feedback is limited as haptic information on grasping strength and tissue stiffness is mostly lost due to internal instrument backlash and friction. This increases tissue trauma risk as excessive grasping forces can lead to (postoperative) complications. This study aims to develop a grasping force feedback providing add-on for a laparoscopic grasper and to validate its impact on skills acquisition in basic laparoscopic skills training. Method: The ShaftFlex, a shaft-based grasping force measurement system providing feedback was designed as an add-on for standard reusable instruments. It consists of a compliant element deflecting proportionally to the applied grasping force, and a Hall sensor measuring that deflection. Influence on skills acquisition was evaluated in a comparative study where novices were divided into a Feedback and No feedback group, performing five training trials of a silicon torus transfer boxtrainer task. Afterwards, both groups performed a post-training task without feedback. Grasping force, time to completion and number of errors were measured. Results: There was a significant difference in mean grasping force between groups for all training trials and the post-training trial. In the Feedback group, there was no significant increase in grasping force when feedback was removed. Conclusion: The ShaftFlex working principle provided a feasible, sustainable method to measure grasping forces exerted by a laparoscopic grasper, enabling immediate haptic feedback. It potentially enhances objective skill assessment, providing feedback on training performance. In a clinical context, the ShaftFlex might be useful in surgery where delicate tissue is grasped.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"1-10"},"PeriodicalIF":4.4,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: To address the limitations of conventional aphasia therapy by developing and clinically evaluating a machine learning based interactive lab for personalized rehabilitation in post-stroke patients. Methods and Procedures: A four week clinical trial was conducted with 27 aphasia patients, randomly assigned to an experimental group ($n=11$ ) using the Language Interactive Lab and a control group ($n=16$ ) receiving conventional therapy. Language performance was assessed using the Chinese Communicative Aphasia Test (CCAT). System interaction data were also used to train classifiers for aphasia severity and recovery tracking. Results: The experimental group showed statistically significant improvements in 7 out of 9 CCAT subtests ($p lt 0.05$ ) and a highly significant total score increase ($p lt 0.001$ ) compared to the control group. Machine learning classifiers achieved up to 91.7% accuracy in predicting aphasia severity and recovery progression. Conclusion: The proposed interactive lab integrates gamified therapy with real time, explainable machine learning assessment, demonstrates clinical efficacy in improving language outcomes, and offers a scalable framework for AI-driven, adaptive neurorehabilitation that has been clinically validated within a hospital setting and designed to align with Taiwan Food and Drug Administration (TFDA) software-as-a-medical-device (SaMD) regulatory principles for translational deployment in clinical environments and hospital investigational use guidelines. Clinical Impact—The integration of gamified digital therapy with machine learning analytics supports personalized, data driven intervention for aphasia rehabilitation in both clinical and home settings, particularly in resource limited environments. Clinical and Translational Impact Statement—This study supports Clinical Research by demonstrating that AI-powered digital therapy significantly improves language outcomes in post-stroke aphasia patients and offers a pathway to scalable, at home neurorehabilitation.
{"title":"Translational Evaluation of a Machine Learning-Based Interactive Lab for Aphasia Rehabilitation in Post Stroke Patients","authors":"Mukul Kumar;Rei-Zhe Wu;Shih-Ching Yeh;Eric Hsiao-Kuang Wu;Po-Yi Tsai","doi":"10.1109/JTEHM.2025.3638643","DOIUrl":"https://doi.org/10.1109/JTEHM.2025.3638643","url":null,"abstract":"Objective: To address the limitations of conventional aphasia therapy by developing and clinically evaluating a machine learning based interactive lab for personalized rehabilitation in post-stroke patients. Methods and Procedures: A four week clinical trial was conducted with 27 aphasia patients, randomly assigned to an experimental group (<inline-formula> <tex-math>$n=11$ </tex-math></inline-formula>) using the Language Interactive Lab and a control group (<inline-formula> <tex-math>$n=16$ </tex-math></inline-formula>) receiving conventional therapy. Language performance was assessed using the Chinese Communicative Aphasia Test (CCAT). System interaction data were also used to train classifiers for aphasia severity and recovery tracking. Results: The experimental group showed statistically significant improvements in 7 out of 9 CCAT subtests (<inline-formula> <tex-math>$p lt 0.05$ </tex-math></inline-formula>) and a highly significant total score increase (<inline-formula> <tex-math>$p lt 0.001$ </tex-math></inline-formula>) compared to the control group. Machine learning classifiers achieved up to 91.7% accuracy in predicting aphasia severity and recovery progression. Conclusion: The proposed interactive lab integrates gamified therapy with real time, explainable machine learning assessment, demonstrates clinical efficacy in improving language outcomes, and offers a scalable framework for AI-driven, adaptive neurorehabilitation that has been clinically validated within a hospital setting and designed to align with Taiwan Food and Drug Administration (TFDA) software-as-a-medical-device (SaMD) regulatory principles for translational deployment in clinical environments and hospital investigational use guidelines. Clinical Impact—The integration of gamified digital therapy with machine learning analytics supports personalized, data driven intervention for aphasia rehabilitation in both clinical and home settings, particularly in resource limited environments. Clinical and Translational Impact Statement—This study supports Clinical Research by demonstrating that AI-powered digital therapy significantly improves language outcomes in post-stroke aphasia patients and offers a pathway to scalable, at home neurorehabilitation.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"13 ","pages":"561-570"},"PeriodicalIF":4.4,"publicationDate":"2025-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271240","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-26DOI: 10.1109/JTEHM.2025.3637293
Yu Meng;Javier Garcia-Casado;Gema Prats-Boluda;Jose Luis Martinez-de-Juan;Carmen Padilla Prieto;Rogelio Monfort-Ortiz;Vicente José Diago-Almela;Dongmei Hao;Guangfei Li;Yiyao Ye-Lin
Objective: Electrohysterography (EHG) has been shown to provide valuable information for assessing preterm birth risk. However, few studies have focused on multiple gestations (MG), a well-known risk factor for preterm birth. This study aimed to comprehensively characterize and compare uterine EHG signals between singleton (SG) and MG pregnancies during the third trimester. Method: This prospective cohort study analyzed 383 EHG recordings from 61 SG and 92 MG women during the third trimester. A whole-window approach was used to extract four key EHG features: peak-to-peak amplitude (PPA), Kurtosis of the Hilbert Envelope (KHE), median frequency (MDF) and sample entropy (SampEn). Generalized additive models (GAM) were applied to evaluate temporal trends across gestational age (GA) and gestation type (SG and MG). Results: In SG pregnancies, PPA and KHE progressively increased, with a significant rise in KHE at labour. MDF remained stable until labour, while SampEn gradually declined, especially at term. MG pregnancies showed similar but less pronounced trends: MG exhibited a notably earlier activation of uterine activity than SG before 32 weeks of gestation (WoG), and a slowing-down electrophysiological progression beyond 32 WoG, resulting in similar characteristics with no significant differences. Conclusion: These findings provide electrophysiological evidence suggesting that MG pregnancies may enter a labour-preparatory state earlier, potentially increasing the PTB risk, while the later convergence of EHG features may indicate compensatory mechanisms to delay labour. This work integrates EHG signal analysis with clinical obstetric care, offering valuable insights for clinical management and early PTB risk assessment in MG pregnancies.
{"title":"A Comprehensive Study of Uterine Muscle Activity During the Third Trimester: Comparison of Singleton and Multiple Gestations","authors":"Yu Meng;Javier Garcia-Casado;Gema Prats-Boluda;Jose Luis Martinez-de-Juan;Carmen Padilla Prieto;Rogelio Monfort-Ortiz;Vicente José Diago-Almela;Dongmei Hao;Guangfei Li;Yiyao Ye-Lin","doi":"10.1109/JTEHM.2025.3637293","DOIUrl":"https://doi.org/10.1109/JTEHM.2025.3637293","url":null,"abstract":"Objective: Electrohysterography (EHG) has been shown to provide valuable information for assessing preterm birth risk. However, few studies have focused on multiple gestations (MG), a well-known risk factor for preterm birth. This study aimed to comprehensively characterize and compare uterine EHG signals between singleton (SG) and MG pregnancies during the third trimester. Method: This prospective cohort study analyzed 383 EHG recordings from 61 SG and 92 MG women during the third trimester. A whole-window approach was used to extract four key EHG features: peak-to-peak amplitude (PPA), Kurtosis of the Hilbert Envelope (KHE), median frequency (MDF) and sample entropy (SampEn). Generalized additive models (GAM) were applied to evaluate temporal trends across gestational age (GA) and gestation type (SG and MG). Results: In SG pregnancies, PPA and KHE progressively increased, with a significant rise in KHE at labour. MDF remained stable until labour, while SampEn gradually declined, especially at term. MG pregnancies showed similar but less pronounced trends: MG exhibited a notably earlier activation of uterine activity than SG before 32 weeks of gestation (WoG), and a slowing-down electrophysiological progression beyond 32 WoG, resulting in similar characteristics with no significant differences. Conclusion: These findings provide electrophysiological evidence suggesting that MG pregnancies may enter a labour-preparatory state earlier, potentially increasing the PTB risk, while the later convergence of EHG features may indicate compensatory mechanisms to delay labour. This work integrates EHG signal analysis with clinical obstetric care, offering valuable insights for clinical management and early PTB risk assessment in MG pregnancies.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"11-18"},"PeriodicalIF":4.4,"publicationDate":"2025-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11269692","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145802383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","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：