IEEE Journal of Translational Engineering in Health and Medicine-Jtehm最新文献

{"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}

{"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}

{"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}

{"title":"KneeMS to Monitor Knee Acoustic Emissions for Juvenile Idiopathic Arthritis","authors":"Ruchik Mishra;Quentin Goossens;Christopher Nichols;Ahmet Rasim Emirdagi;Chuoqi Chen;Onur Selim Kilic;Mohammad Nikbakht;Prabhkirat Bindra;Catherine Yang;Cate Garretson;Lori Ponder;Sampath Prahalad;Omer T. Inan","doi":"10.1109/JTEHM.2026.3721498","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3721498","url":null,"abstract":"Objective: Wearable sensing for capturing knee acoustic emissions (KAEs) can enable earlier detection and better management of juvenile idiopathic arthritis (JIA). In this paper, we expand on our previous work by validating the KneeMS wearable for individuals with JIA in a clinical setting against a benchtop system (Dytran).Methods and procedures: Acoustic features were recorded from the medial and lateral sides of the patellar tendon using both Dytran and KneeMS in 36 participants with JIA during flexion/extension (FE). We calculated the Spearman correlation coefficient (<inline-formula> <tex-math>$rho $ </tex-math></inline-formula>) between the acoustic features of both devices Acoustic features were recorded from the medial and lateral sides of the patellar tendon using both Dytran and KneeMS in 36 participants with JIA during flexion/extension (FE). We calculated the Spearman correlation coefficient between the acoustic features of both devices and assessed severity trends and longitudinal tracking of JIA knees from a machine learning (ML) pipeline differentiating active from inactive JIA knees.Results: Of 36 extracted features, six had the highest <inline-formula> <tex-math>$rho $ </tex-math></inline-formula> (medial/lateral): RMS (0.79/0.70), MFCC1 (0.79/0.72), spectral slope (0.78/0.68), energy (0.78/0.67), Hjorth activity (0.75/0.71), and spectral flux (0.74/0.69). Our ML pipeline demonstrated an area under the receiver operating characteristic curve (AUC-ROC) mean of 0.77 (<inline-formula> <tex-math>$plt 0.05$ </tex-math></inline-formula>) and showed a significant (<inline-formula> <tex-math>$plt 0.05$ </tex-math></inline-formula>) upward trend in active knee prediction probabilities <inline-formula> <tex-math>$P(A)$ </tex-math></inline-formula> with clinical severity using KneeMS. For follow-ups, KneeMS <inline-formula> <tex-math>$P(A)$ </tex-math></inline-formula> moved in the clinically expected direction for 4 of 5 status-changing knees (versus 1 of 5 for Dytran); the clinical JADAS (cJADAS) score, available for most knees, was consistent with this finding.Conclusion: The high correlation between the acoustic features of Dytran and KneeMS, a significant AUC-ROC, significant JIA severity trend, and prospective longitudinal tracking make KneeMS a viable alternative to Dytran.Clinical impact: This validation establishes the foundation of home-based longitudinal joint assessment for JIA.Clinical and Translational Impact Statement: Wearable acoustic monitoring could enable at-home tracking of JIA disease activity, supporting timely treatment.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"369-379"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11644703","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836850","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}

{"title":"Early Sound-Based Meal Onset Detection Using Hidden Markov Models (HMMs)","authors":"Laura Lema-Pérez;Maja Grauff Erntsen;Øyvind Stavdahl;Anders Lyngvi Fougner","doi":"10.1109/JTEHM.2026.3732514","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3732514","url":null,"abstract":"Objective: Meal detection is essential for automated insulin delivery systems in patients with Type 1 Diabetes (T1D), as meals are the primary drivers of rapid postprandial glucose excursions. Current closed-loop systems depend on manual meal announcements, which are often inaccurate or omitted, reducing safety and autonomy. To address this, we developed an automatic meal detector leveraging physiological sound sequences from the body. Methods and procedures: The dataset comprised 50 meal recordings from ten participants (aged 24–30 years) using a throat-mounted microphone. Twenty recordings were collected in quiet conditions, while 30 included deliberate, realistic disturbances. Audio signals were preprocessed, segmented, and transformed into 46 features. Linear Discriminant Analysis (LDA) was implemented as a benchmark, while continuous Hidden Markov Model (HMM)s were applied to capture temporal dependencies and estimate meal onset probability. Results: Performance was evaluated using both an 80:20 train-test split and Leave-One-Subject-Out Cross-Validation (LOSO CV). Explainable Artificial Intelligence (XAI) techniques were employed to interpret model behavior and identify informative features of meal events. LDA achieved 90% accuracy, 78% sensitivity, and a detection delay of 12.3 s, while HMM reached 91% for both accuracy and sensitivity, with an average detection time of 11.7 s. Both models performed well under quiet conditions but were sensitive to background disturbances. Conclusion: These findings demonstrate the feasibility of detecting meal onset from physiological sounds. XAI analysis revealed that HMM effectively captures sequential transitions associated with chewing and swallowing, offering interpretable insights beyond non-temporal methods. Thus, HMM shows potential as a rapid, context-aware meal classifier for closed-loop insulin therapy, thanks to its effective modeling of temporal structure. Clinical Impact: This pilot study uses an innovative throat-mounted microphone to detect early meal intake by capturing chewing and swallowing sounds, offering an alternative to traditional measures such as continuous glucose monitoring (CGM).","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"410-424"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11686004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149188291","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}

{"title":"Clinical Correlation of Smart IoT-Enabled Point-of-Care wIT Jacket With Plethysmograph","authors":"Vaishali Sharma;Mayank Goswami;Ruchi Dua","doi":"10.1109/JTEHM.2026.3654554","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3654554","url":null,"abstract":"Background: Conventional pulmonary function tests, often considered the gold standard, are time-consuming, typically yield only graphical or numerical data, and requiring significant effort from patients and often require clinical setups. Purpose: To develop an Industry 4.0 ready IoT-enabled, AI-assisted, point-of-care impedance tomography based jacket featuring wireless connectivity (wIT) for dynamic monitoring the human lung functions via an android smartphone interface and clinically evaluate its diagnostic performance against standard PFT modalities. Methods: A total of forty-six individuals (23 control and 23 patients) were included in this study, registered under the clinical trial registry of India, and two involved IHEC Committees. Standard pulmonary physiological parameters, including primary lung volumes (Functional Residual Capacity, Inspiratory Capacity, Total Lung Capacity, and Residual Volume), as well as secondary volumes (Expiratory Reserve Volume and Vital Capacity), were obtained from Plethysmography, Spirometry, and the wIT jacket. The wIT measurements were recorded simultaneously with these PFT, and results obtained by AI trained model were statistically compared to assess correlation and diagnostic performance. Results: The wIT system achieved a sensitivity of 78%, a specificity of 86%, a positive predictive value of 86%, and a negative predictive value of 80%, as derived from the confusion matrix. In comparison, the corresponding values for spirometry were 23%, 90%, 22%, and 91%, and for plethysmography were 95.2%, 81.7%, 66.4%, and 97.8%. Matthew’s correlation coefficient of 0.6547 further confirmed the classification reliability of the wIT jacket. Conclusion: The developed wIT system exhibited the ability to reliably classify subjects as healthy or not healthy. It established agreement with body plethysmography measurements. A frequency-based imaging biomarker for wIT is developed. The study demonstrated devices’ potential that may be used as a non-invasive: (a) point-of-care device in non-clinical environment and/or (b) add-on with existing gold standard clinical setups, for pulmonary assessment and long-term respiratory monitoring. Clinical Impact—This work presents a non-invasive, IoT-enabled, compact, and portable wIT device for pulmonary function testing. In contrast to traditional methods such as spirometry and body plethysmography, which are often bulky and limited to clinical environments, this device offers a more accessible and userfriendly solution. It not only measures lung function but also provides corresponding imaging, enabling a more comprehensive assessment. This approach has strong potential to enhance early diagnosis, continuous monitoring, and overall accessibility of lung health evaluation, particularly essential for remote or resourceconstrained settings. Clinical and Translational Impact Statement—This study integrates AI-driven lung segmentation to achieve accurate lung volume estimation, significa","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"435-444"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11354531","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149249539","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}

{"title":"Integrative Machine Learning of Genetic and Lifestyle Factors for Personalized Skin Health","authors":"Yassine Benachour;Lina Maloukh;Barbara Geusens","doi":"10.1109/JTEHM.2026.3675676","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3675676","url":null,"abstract":"Objective: To develop an AI framework that combines genetic, phenotypic, and lifestyle data for profiling skin-health patterns and generating hypothesis-supporting summaries for potential decision support.Methods and procedures: A dataset of 5,254 individuals integrates six genes (FLG, AQP3, MMP-1, MMP-3, SOD2, GPX), six phenotype severities, and 20+ lifestyle factors. Mutation burden and interactions are tested by ANOVA. K-modes clustering identifies four interpretable dermatological profiles within the cohort and is embedded in leakage-free nested cross-validation (train-only selection; test labels from training centroids). Subtypes are predicted from genetics plus lifestyle using an XGBoost (XGB) classifier; explainability uses gain, permutation importance, and SHAP contributions aggregated across outer folds.Results: Four subtypes are identified. Mutation burden differed across phenotypes (ANOVA, <inline-formula> <tex-math>$plt 0.05$ </tex-math></inline-formula>). Interactions are observed for AQP3<inline-formula> <tex-math>$times $ </tex-math></inline-formula>Winter<inline-formula> <tex-math>$rightarrow $ </tex-math></inline-formula>Dryness, GPX<inline-formula> <tex-math>$times $ </tex-math></inline-formula>Medication<inline-formula> <tex-math>$rightarrow $ </tex-math></inline-formula>Pigmentation, and MMP-3<inline-formula> <tex-math>$times $ </tex-math></inline-formula>City Living<inline-formula> <tex-math>$rightarrow $ </tex-math></inline-formula>Redness. Nested-CV prediction achieves <inline-formula> <tex-math>$0.9789pm 0.0083$ </tex-math></inline-formula> accuracy with macro-F<inline-formula> <tex-math>$1~0.9711pm 0.0126$ </tex-math></inline-formula> and macro-recall <inline-formula> <tex-math>$0.9697pm 0.0091$ </tex-math></inline-formula>. This outperformed unimodal baselines and improved generalization across all folds in practice. Drivers are stable across folds and included scrub usage, stress, sleep, low water intake, menopause, and camouflage habits, alongside oxidative-stress and MMP genes.Conclusion: Integrating genomic susceptibility with modifiable exposures enables robust, interpretable skin-profile prediction and highlights actionable targets for stratified counseling beyond genetic predisposition.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"164-178"},"PeriodicalIF":4.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11447225","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557697","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}

{"title":"Development and Bench-to-Human Feasibility Evaluation of a Wireless Pinch-and-Grip Dynamometer","authors":"Ali Pourhossein;Mohamed Mehdi Ouerghi;Elisabeth Kuborn;Doguhan Tasdemir;Viktor Warwas;Charmayne Mary Lee Hughes","doi":"10.1109/JTEHM.2026.3720716","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3720716","url":null,"abstract":"Objective: This study presents MeRKeL, a portable wireless system designed for quantitative, reference-calibrated assessment of pinch and grip strength, and evaluates its technical validity and human feasibility under standardized laboratory conditions.Methods: The system consists of two compact and functionally aligned modules (pinch and grip dynamometer) sharing a unified electronic architecture and data acquisition pipeline. Both employ task-specific mechanical designs tailored to the distinct loading characteristics of pinch and grip actions. Reference-based calibration and bench validation were performed across the full operating ranges and across multiple units. Accuracy, agreement, and within-session repeatability were evaluated using root mean squared error (RMSE), Bland–Altman analysis, and intraclass correlation coefficient (ICC). Feasibility testing in 196 healthy adults examined associations between maximal strength and demographic, behavioral, and health-related variables.Results: Bench validation showed high agreement with the calibrated reference instrument (pinch: RMSE = 0.95 N, bias <inline-formula> <tex-math>$= -0.56$ </tex-math></inline-formula> N; grip: RMSE = 1.86 N, bias <inline-formula> <tex-math>$= -1.10$ </tex-math></inline-formula> N), and within-session repeatability was excellent (MDC95 pinch = 0.86 N; grip = 1.43 N). Experimental testing reproduced expected associations with key demographic and behavioral factors.Conclusion: The MeRKeL system enables accurate and repeatable, reference-calibrated wireless measurement of pinch and grip strength, establishing a robust technical foundation for subsequent clinical evaluation and future home-based neuromuscular monitoring studies.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"330-338"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11643790","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148747861","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}

{"title":"Evaluation of a Wrist-Worn Device for ECG-Based Detection of Acute Myocardial Infarction","authors":"Karolina Eitminavičienė;Daivaras Sokas;Žygimantas Abramikas;Džiugilė Kersnauskaitė;Dominika Širvienė;Artiomas Širvys;Guostė Stankevičiūtė;Vytautas Juknevičius;Justinas Bacevičius;Leif Sörnmo;Andrius Petrėnas","doi":"10.1109/JTEHM.2026.3730465","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3730465","url":null,"abstract":"Objective: To determine whether a two-lead ECG (wECG), acquired using a self-applicable, wrist-worn device, provides diagnostic value in acute myocardial infarction (AMI) detection. Methods: Seventy-one patients with AMI, 26 with other cardiovascular diseases (CVDs), and 54 healthy controls were enrolled in the study. To acquire lead I, one electrode of the wrist-worn device was touched with the index finger of the opposite hand, while another lead was acquired by touching the electrode on the strap to a specific part of the body. The diagnostic value of the wECG is evaluated either directly or through synthesis of the standard 12-lead ECG using an echo state network. Results: Using the standard ECG, an AMI detector based on a convolutional neural network yields a sensitivity of 0.86 and a specificity of 0.71; the corresponding figures for blinded cardiologist diagnosis are 0.77/0.88. Using the synthesized ECG, the V3 electrode touch site yields the best performance, with a sensitivity/specificity of 0.84/0.71 for AMI detection and 0.67/0.86 for cardiologist diagnosis. Compared to the synthesized ECG across all touch sites, use of the wECG results in a substantially lower sensitivity, reduced by 0.12–0.13, while the specificity is comparable or slightly higher. Implementation of a two-stage approach, consisting of detector-based screening followed by cardiologist review of positive cases, results in correct decisions in 63% of the AMI cases using either the synthesized ECG or the wECG. Conclusion: The two-lead ECG acquired with a wrist-worn device offers diagnostic value and enables screening for AMI.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"380-389"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11677135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149131329","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}

{"title":"Computerized Platform in Hindi Language: Exploring Its Use in Aphasia Screening","authors":"Paromita Mitra;Shipra Kethwalia;Rhythm Makkar;Ruchita Hazrati;Rahul Chhatlani;Geetesh Kumar Singh;Ashima Nehra;Uttama Lahiri","doi":"10.1109/JTEHM.2026.3733827","DOIUrl":"https://doi.org/10.1109/JTEHM.2026.3733827","url":null,"abstract":"Objective: Aphasia is a frequent sequela of stroke, affecting approximately 25%–40% of stroke survivors due to focal damage to language-related brain regions. In resource-constrained settings like India, timely screening is limited by the cost of neuroimaging and the time-intensive nature of conventional pen-and-paper assessments. This study presents a Computerized Hindi Aphasia Screening Platform offering various tasks (CHASP), a computer-based multimodal screening platform designed to objectively differentiate aphasic and non-aphasic post-stroke individuals from healthy controls. Methods: CHASP integrates Acoustic, and Visual and Reading tasks with a sensor-enabled base station for response-time quantification and a physiology-based module for acquiring photoplethysmography-derived interbeat interval (IBI) as a biomarker of cognitive processing. Post-stroke participants were independently assessed using the Western Aphasia Battery (WAB), the gold-standard clinical tool. Performance scores from CHASP and relevant sections of WAB were compared for exploring clinical relevance. Results: The CHASP task modules reliably differentiated post-stroke participants from healthy controls across performance scores, response times, and IBI. The Acoustic tasks could distinguish the aphasic and non-aphasic groups, particularly through task scores and IBI measures. Strong correlations were observed between CHASP performance scores and corresponding WAB scores, supporting the clinical validity of the proposed platform.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"14 ","pages":"425-434"},"PeriodicalIF":3.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11690915","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149188116","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}