Search Results (135)

Traditional cuff-based blood pressure (BP) monitoring methods provide only intermittent readings, while invasive alternatives pose clinical risks. Recent studies have demonstrated feasibility of estimating continuous non-invasive cuff-less BP using photoplethysmogram (PPG) signals alone. However, existing approaches rely on complex manual feature engineering and/or multiple model architectures, resulting in inefficient epoch training numbers and limited performance. This research proposes cBP-Tnet, an efficient single-channel and model multi-task Transformer network designed for PPG signal automatic feature extraction. cBP-Tnet employed specialized hyperparameters—integrating adaptive Kalman filtering, outlier elimination, signal synchronization, and data augmentation—leveraging multi-head self-attention and multi-task learning strategies to identify subtle and shared waveform patterns associated with systolic blood pressure (SBP) and diastolic blood pressure (DBP). We used the MIMIC-II public dataset (500 patients with 202,956 samples) for experimentation. Results showed mean absolute errors of 4.32 mmHg for SBP and 2.18 mmHg for DBP. For the first time, both SBP and DBP meet the Association for the Advancement of Medical Instrumentation’s international standard (<5 mmHg, >85 subjects). Furthermore, the network efficiently reduces the epoch training number by 13.67% when compared to other deep learning methods. Thus, this establishes cBP-Tnet’s potential for integration into wearable and home-based healthcare devices with continuous non-invasive cuff-less blood pressure monitoring. Full article

Cardiovascular disease (CVD) is the leading cause of global mortality, with hypertension affecting over one billion people. Current noninvasive blood pressure (BP) systems, like cuffs, suffer from discomfort and placement errors and lack continuous monitoring. Wearable solutions promise improvements, but technologies like photoplethysmography (PPG) and bioimpedance (BIOZ) face usability and clinical accuracy limitations. PPG is sensitive to skin tone and body mass index (BMI) variability, while BIOZ struggles with electrode contact and reusability. We present a novel, strain gauge-based wearable BP device that directly quantifies pressure via a dual transducer system, compensating for tissue deformation and external forces to enable continuous, accurate BP measurement. The reusable, energy-efficient, and compact design suits long-term daily use. A novel leg press protocol across 10 subjects (systolic: 71.04–241.42 mmHg, diastolic: 53.46–123.84 mmHg) validated its performance under dynamic conditions, achieving mean absolute errors of 2.45 ± 3.99 mmHg (systolic) and 1.59 ± 2.08 mmHg (diastolic). The device showed enhanced robustness compared to the Finapres, with less motion-induced noise. This technology significantly advances current methods by delivering continuous, real-time BP monitoring without reliance on electrodes, independent of skin tone, while maintaining a high accuracy and user comfort. Full article

Cardiovascular disease is a major health threat closely associated with blood pressure levels. While continuous monitoring is essential, traditional cuff-based devices are inconvenient for long-term use. Current methods often fail to balance deep learning capabilities with interpretability, limiting further accuracy improvements. To address this problem, we propose a novel two-branch deep learning framework combining Residual Networks (ResNet) and Bidirectional Long Short-Term Memory (BiLSTM) for photoplethysmography (PPG)-based cuffless blood pressure estimation. The ResNet branch processes 60 features selected by Support Vector Machine-Recursive Feature Elimination (SVM-RFE) from manually extracted features, including our newly proposed trend features, while the BiLSTM branch processes complete PPG waveforms. Testing on 220 waveform segments from 218 patients in the MIMIC-IV dataset, our method achieves mean absolute errors of 3.47 mmHg and 2.81 mmHg, with standard deviations of 5.06 mmHg and 4.11 mmHg for systolic and diastolic blood pressure. This performance meets the Association for the Advancement of Medical Instrumentation (AAMI) standards and achieves an A rating according to British Hypertension Society (BHS) standards. Full article

(1) Background: The use of wearable cuffless devices has emerged as an out-of-office blood pressure (BP) monitor device to improve the management of hypertension. We aimed to validate a new, low-cost smartwatch for the measurement of BP and, secondarily, to assess its reliability for the measurement of blood oxygen saturation (SpO₂) and heart rate. (2) Methods: We compared 1000 pairs of measurements (n = 100) acquired by a smartwatch (KC08) with those measured by a reference device. (3) Results: A total of 100 participants (41 ± 18 years) completed the measurements. The values for the systolic and diastolic BP, heart rate and SpO₂ measured with the Smartwatch KC08 and the reference devices differed significantly (p < 0.05). In addition, the Smartwatch KC08 showed a low variability and poor reliability for all the assessed outcomes except for the heart rate. Moreover, no significant heteroscedasticity was observed for the heart rate measured by the Smartwatch KC08 and the reference sphygmomanometer. (4) Conclusions: The main findings of the present study suggest that the Smartwatch KC08 is not yet suitable for daily clinical practice, although it showed low intra-subject variability and reliability for the resting heart rate. Full article

Background and Objectives: Many middle-aged and older individuals experience shoulder pain, often due to partial-thickness rotator cuff tears (PTRCTs). If conservative treatment fails to relieve symptoms in a patient, surgical intervention may be necessary. In such cases, using a bioinductive collagen implant may offer a viable alternative to conventional rotator cuff repair. Most notably, it offers potential advantages, particularly in reducing postoperative pain and promoting faster recovery. Accordingly, this study aims to evaluate the clinical outcomes of treating bursal-sided partial-thickness rotator cuff tears using bioinductive collagen implants alone, without concurrent rotator cuff repair. Materials and Methods: We followed 32 patients who had bursal-sided partial-thickness rotator cuff tears (Ellman grade I or II) and received conservative care for more than six months but continued to experience symptoms. These patients received surgery using bioinductive collagen implants without rotator cuff repair, and we followed up on their postoperative prognosis for at least one year after surgery. For a more accurate contrast, we performed clinical evaluation preoperatively and at 2 weeks, 6 weeks, 3 months, 6 months, and 12 months postoperatively. Visual Analog Scale (VAS), American Shoulder and Elbow Surgeons (ASES) score, Single Assessment Numeric Evaluation (SANE), and Western Ontario Rotator Cuff (WORC) score were used as assessment tools in this study. As for radiological outcomes, magnetic resonance imaging (MRI) and ultrasonography were helpful. This supported our assessment of graft integration and failure. Results: These 32 patients included 13 with Ellman grade I tear and 19 with grade II tear. In both cases, they underwent surgery only using bioinductive collagen implants, and any anchor-based cuff repair was completely excluded. As for VAS (3.8 ± 2.9), certain statistically significant improvements were found starting at 2 weeks postoperatively. On the other hand, the scores of ASES (58.6 ± 20.3), SANE (60.1 ± 23.2), and WORC (59.8 ± 22.4) began to indicate a significant improvement starting at 6 weeks postoperatively (p < 0.001), showing continuous progress. At each final step, we confirmed that there were no cases of graft failure by radiological evaluation and found successful healing indicators, such as much less pain in all patients. Conclusions: The findings of this study provide the clinical evidence that a surgery using bioinductive collagen implant for bursal-sided partial-thickness rotator cuff tears is a highly effective treatment option in patients unresponsive to conservative therapy. Particularly, its practical clinical effectiveness includes facilitating rapid recovery without a significant risk of complications. Full article

Cuffless continuous blood pressure (BP) monitoring is essential for personal health management. However, its accuracy is challenged by the diversity and heterogeneity of physiological data sources. We propose a multi-source feature selection framework based on Markov blanket theory and the concept of causal invariance. We extracted 218 BP-related photoplethysmography (PPG) features from three heterogeneous datasets (differing in subject population, acquisition devices, and methods) and constructed a causal feature set using the Multi-Dataset Stable Feature Selection via Ensemble Markov Blanket (MDSFS-EMB) algorithm. BP estimation was then performed using four machine learning models. The MDSFS-EMB algorithm integrated PPFS and HITON-MB, enabling adaptability to different data scales and distribution scenarios. It employed Gaussian Copula Mutual Information, which was robust to outliers and capable of modeling nonlinear relationships. To validate the effectiveness of the selected feature set, we conducted experiments using an independent external validation dataset and explored the impact of data segmentation strategies on model prediction outcomes. The results demonstrated that the MDSFS-EMB algorithm has advantages in feature selection efficiency, prediction accuracy, and generalization capability. This study innovatively explores the causal relationships between PPG features and BP across multiple data sources, providing a clinically applicable approach for cuffless BP estimation. Full article

Nocturnal monitoring of continuous, cuffless blood pressure (BP) can unleash a whole new world for the prognostication of cardiovascular and other diseases due to its strong predictive capability. Nevertheless, the lack of an accurate and reliable method, primarily due to confounding variables, has prevented its widespread clinical adoption. Herein, we demonstrate how optimized machine learning using the Catch-22 features, when applied to the photoplethysmogram waveform and personalized with direct BP data through transfer learning, can accurately estimate systolic and diastolic BP. After training with a hemodynamically compromised VitalDB “calibration-free” dataset (n = 1293), the systolic and diastolic BP tested on a distinct VitalDB dataset that met AAMI criteria (n = 116) had acceptable error biases of −1.85 mm Hg and 0.11 mm Hg, respectively [within the 5 mm Hg IEC/ANSI/AAMI 80601-2-30, 2018 standard], but standard deviation (SD) errors of 19.55 mm Hg and 11.55 mm Hg, respectively [exceeding the stipulated 8 mm Hg limit]. However, personalization using an initial calibration data segment and subsequent use of transfer learning to fine-tune the pretrained model produced acceptable mean (−1.31 mm Hg and 0.10 mm Hg) and SD (7.91 mm Hg and 4.59 mm Hg) errors for systolic and diastolic BP, respectively. Levene’s test for variance found that the personalization method significantly outperformed (p < 0.05) the calibration-free method, but there was no difference between three machine learning methods. Optimized multimodal Catch-22 features, coupled with personalization, demonstrate great promise in the clinical adoption of continuous, cuffless blood pressure estimation in applications such as nocturnal BP monitoring. Full article

(1) Background: Blood pressure (BP) variability is an important risk factor for cardiovascular diseases. Still, existing BP monitoring methods often require periodic cuff-based measurements, raising concerns about their accuracy and convenience. This study aims to develop a subject-independent, cuff-less BP estimation method using finger and toe photoplethysmography (PPG) signals combined with an electrocardiogram (ECG) without the need for an initial cuff-based measurement. (2) Methods: A customized measurement system was used to record 80 readings from human subjects. Fifteen features with the highest dependency on the reference BP, including time and morphological characteristics of PPG and subject information, were analyzed. A multivariate regression model was employed to estimate BP. (3) Results: The results showed that incorporating toe PPG signals improved the accuracy of BP estimation, reducing the mean absolute error (MAE). Using both finger and toe PPG signals resulted in an MAE of 9.63 ± 12.54 mmHg for systolic BP and 6.76 ± 8.38 mmHg for diastolic BP, providing the lowest MAE compared to previous methods. (4) Conclusions: This study is the first to integrate toe PPG for more accurate BP estimation and proposes a method that does not require an initial cuff-based BP measurement, offering a promising approach for non-invasive, continuous BP monitoring. Full article

Background: Deep learning (DL) reconstruction techniques have shown promise in reducing MRI acquisition times while maintaining image quality. However, the impact of different acceleration factors on diagnostic accuracy in shoulder MRI remains unexplored in clinical practice. Purpose: The purpose of this study was to evaluate the diagnostic accuracy of 2-fold and 4-fold DL-accelerated shoulder MRI protocols compared to standard protocols in clinical practice. Materials and Methods: In this prospective single-center study, 88 consecutive patients (49 males, 39 females; mean age, 51 years) underwent shoulder MRI examinations using standard, 2-fold (DL2), and 4-fold (DL4) accelerated protocols between June 2023 and January 2024. Four independent radiologists (experience range: 4–25 years) evaluated the presence of bone marrow edema (BME), rotator cuff tears, and labral lesions. The sensitivity, specificity, and interobserver agreement were calculated. Diagnostic confidence was assessed using a 4-point scale. The impact of reader experience was analyzed by stratifying the radiologists into ≤10 and >10 years of experience. Results: Both accelerated protocols demonstrated high diagnostic accuracy. For BME detection, DL2 and DL4 achieved 100% sensitivity and specificity. In rotator cuff evaluation, DL2 showed a sensitivity of 98–100% and specificity of 99–100%, while DL4 maintained a sensitivity of 95–98% and specificity of 99–100%. Labral tear detection showed perfect sensitivity (100%) with DL2 and slightly lower sensitivity (89–100%) with DL4. Interobserver agreement was excellent across the protocols (Kendall’s W = 0.92–0.98). Reader experience did not significantly impact diagnostic performance. The area under the ROC curve was 0.94 for DL2 and 0.90 for DL4 (p = 0.32). Clinical Implications: The implementation of DL-accelerated protocols, particularly DL2, could improve workflow efficiency by reducing acquisition times by 50% while maintaining diagnostic reliability. This could increase patient throughput and accessibility to MRI examinations without compromising diagnostic quality. Conclusions: DL-accelerated shoulder MRI protocols demonstrate high diagnostic accuracy, with DL2 showing performance nearly identical to that of the standard protocol. While DL4 maintains acceptable diagnostic accuracy, it shows a slight sensitivity reduction for subtle pathologies, particularly among less experienced readers. The DL2 protocol represents an optimal balance between acquisition time reduction and diagnostic confidence. Full article

Objectives: Metal anchors (MA), commonly used in the early stages of rotator cuff surgical treatment development, are associated with a high risk of complications, especially in osteoporotic bone. As an alternative to rigid anchors, all-suture anchors (ASA) have been introduced for the medial row, offering promising clinical outcomes and favorable biomechanical studies. We aimed to compare the clinical outcomes of MAs and ASAs in either single-row or in medial-row suture bridge techniques in arthroscopic rotator cuff repair. Our hypothesis was that in cases where ASA was used for at least 12 months of follow-up, more favorable results would be obtained as compared to rigid anchors, and intraoperative complications such as anchor pullout would be encountered less. Methods: In this retrospective cohort analysis, we reviewed patients who underwent arthroscopic rotator cuff repair between January 2020 and December 2022. Surgeries were performed by two senior surgeons in a single tertiary center. Patients who had undergone revision surgery, had a history of previous shoulder surgeries, had massive rotator cuff tears, and partial-thickness tears; or had concomitant subscapularis tears were excluded. Preoperative and postoperative scores, including Constant–Murley (CM), Disabilities of the Arm, Shoulder, and Hand (DASH), and visual analog scale (VAS), were compared. The minimum follow-up period was 12 months. Clinical assessment of shoulder range of motion included forward flexion, abduction, internal rotation, and external rotation. Intraoperative anchor-related complications were compared. All patients underwent the same surgical technique and postoperative rehabilitation protocol. Results: A total of 142 patients (89 females, 53 males; mean age: 57.4 years) were included in the study, with 67 patients in the ASA group and 75 in the MA group. The sex distribution and mean age were similar between groups. The ASA group had 15 traumatic tears, while the MA group had 13 (p < 0.05). The mean follow-up period was 21.6 months (range 12–40 months). Preoperative CM scores were statistically better in the ASA group, but this difference was not clinically relevant (p < 0.046). The mean CM score was 75.64, the mean DASH score was 8.57, and the mean VAS was 1.38 at the postoperative period in the MA group. The mean CM score was 78.40, the mean DASH score was 9.75, and VAS was 1.59 at the postoperative period in the ASA group. Seven cases experienced anchor pullout in the MA group, and thread breakage occurred in one patient of each group (p = 0.014). The mean age of the patients with anchor pullout was significantly higher (p = 0.002). This finding was not hypothesized in the initial study design but emerged during post-hoc analysis and highlights the importance of considering bone quality in elderly patients. Conclusions: The clinical outcomes of rotator cuff repairs using all-suture anchors or metal anchors are comparable. However, ASA use may offer an advantage in elderly patients by reducing the risk of anchor pullout. Further studies assessing tendon integrity and bone quality and incorporating long-term follow-up periods are recommended to support and validate the present findings. Full article

Metabolic syndrome (MetS) associated with Osteoarthritis (OA) is an increasingly recognised entity. Whilst the degenerative pattern in cuff-tear arthropathy (CTA) has been well documented, the biological processes behind primary shoulder OA and CTA remain less understood. This study investigates transcriptomic differences in these conditions, alongside the impact of MetS in patients undergoing total shoulder replacement. In a multi-centre study, 20 OA patients undergoing total shoulder replacement were included based on specific treatment indications for OA and cuff-tear arthropathy as well as 25 patients undergoing rotator cuff repair (RCR) as a comparator group. Tissues from subchondral bone, capsule (OA and RCR), and synovium were biopsied, and RNA sequencing was performed using Illumina platforms. Differential gene expression was conducted using DESeq2, adjusting for demographic factors, followed by pathway enrichment using the mitch package. Gene expressions in CTA and primary OA was differentially affected. CTA showed mitochondrial dysfunction, GATD3A downregulation, and increased cartilage degradation, while primary OA was marked by upregulated inflammatory and catabolic pathways. The effect of MetS on these pathologies was further shown. MetS further disrupted WNT/β-catenin signalling in CTA, and in OA. Genes such as ACAN, PANX3, CLU, and VAT1L were upregulated, highlighting potential biomarkers for early OA detection. This transcriptomic analysis reveals key differences between end-stage CTA and primary glenohumeral OA. CTA shows heightened metabolic/protein synthesis activity with less immune-driven inflammation. Under MetS, mitochondrial dysfunction (including GATD3A downregulation) and altered Wnt/β-catenin signalling intensify cartilage and bone damage. In contrast, primary OA features strong complement activation, inflammatory gene expression, and collagen remodelling. MetS worsens both conditions via oxidative stress, advanced glycation end products, and ECM disruption—particularly, increased CS/DS degradation. These distinctions support targeted treatments, from antioxidants and Wnt modulators to aggrecanase inhibitors or clusterin augmentation. Addressing specific molecular disruptions, especially those amplified by MetS, may preserve shoulder function, delay surgical intervention, and improve long-term patient outcomes. Full article

Background: Over the season, competitive swimmers experience a progressive imbalance in rotator cuff strength, predisposing them to a significant risk factor for a swimmer’s shoulder injury. Objectives: Verify the effectiveness of two 12-week preventive programs on the shoulder rotators’ peak torque and conventional/functional ratios. Design: A care provider- and participant-blinded, parallel, randomized controlled trial with three groups. Participants: Competitive swimmers aged 16 to 35 years with no prior clinical issues related to their shoulders. Interventions: Twice a week, over 12 weeks, the two experimental groups performed five exercises where the only difference was executing the program with weights or elastic bands, and the control group performed a sham intervention. Main outcome measures: The concentric and eccentric peak torque of the internal and external rotators of the dominant shoulder were assessed before and after the intervention using an isokinetic dynamometer Biodex System 3, at 60°/s, 120°/s, and 180°/s. Results: Among the experimental groups, only one test indicated a reduction (p ≤ 0.05) in rotator peak torque, while the control group showed a decrease (p ≤ 0.05) in five tests. Swimmers who completed the prevention programs demonstrated less imbalance in conventional/functional ratios than controls. Conclusions: Implementing a 12-week preventive program minimizes the progressive shoulder rotational imbalance over the season in competitive swimmers. Clinical Trial Registration number: NCT06552585. Full article

Background: Rotator cuff-related shoulder pain (RCRSP) is a prevalent musculoskeletal issue, encompassing various shoulder conditions. While exercise typically forms the foundation of conservative treatment, there exists ongoing discourse regarding the effectiveness and role of passive treatments. International guidelines recommend initial conservative management, with surgery considered only after failed conservative treatment. However, recent studies reveal discrepancies between recommended practices and actual clinical management. The aim of the study was to assess current practices in managing RCRSP among Greek physiotherapists, with a focus on understanding the alignment of these practices with international guidelines for conservative treatment. Methods: A cross-sectional survey was conducted among Greek physiotherapists to assess current practices in managing RCRSP. The survey, adapted from previous studies, collected demographic data and assessed clinical reasoning through a vignette-based approach. Responses were analyzed for alignment with guideline-recommended care. Results: Out of over 9000 contacted physiotherapists, 163 responded. A majority expressed a specific interest in shoulder pain (85%). Patient education (100%) and exercise (100%) were widely endorsed, with limited support for imaging (44%), injection (40%), and surgery (26%). Younger respondents were less inclined towards surgical referral (p = 0.001). Additionally, adjunctive interventions like mobilization (66%) and massage therapy (58%) were commonly employed alongside exercise and education. Treatment duration typically ranged from 6 to 8 weeks, with exercises reviewed weekly. Conclusions: The study highlights a consistent preference for conservative management among Greek physiotherapists, aligning with international guidelines. However, there are variations in practice, particularly regarding adjunctive interventions and exercise prescription parameters. Notably, there is a disparity between recommended and actual use of certain modalities. Full article

This paper presents a method to improve confidence-interval (CI) estimation using individual uncertainty measures and weighted feature decisions for cuff-less blood-pressure (BP) measurement. We obtained uncertainty using Gaussian process regression (GPR). The CI obtained from the GPR model is computed using the distribution of BP estimates, which provides relatively wide CIs. Thus, we proposed a method to obtain improved CIs for individual subjects by applying bootstrap and uncertainty methods using the cuff-less BP estimates of each subject obtained through GPR. This study also introduced a novel method to estimate cuff-less BP with high fidelity by determining highly weighted features using weighted feature decisions. The standard deviation of the proposed method’s mean error is 2.94 mmHg and 1.50 mmHg for systolic blood pressure (SBP) and (DBP), respectively. The mean absolute error results were obtained by weighted feature determination combining GPR and gradient boosting algorithms (GBA) for SBP (1.46 mmHg) and DBP (0.69 mmHg). The study confirmed that the BP estimates were within the CI based on the test samples of almost all subjects. The weighted feature decisions combining GPR and GBA were more accurate and reliable for cuff-less BP estimation. Full article

Background/Objectives: This study investigates the potential of Pulse Transit Time (PTT) derived from Impedance Plethysmography (IPG), Photoplethysmography (PPG), and Electrocardiography (ECG) for non-invasive and cuffless blood pressure monitoring. IPG measures blood volume changes through electrical conductivity, while PPG detects variations in microvascular blood flow, providing essential insights for wearable health monitoring devices. Methods: Data were collected from 100 healthy participants under resting and post-exercise conditions using a custom IPG system synchronized with ECG, PPG, and blood pressure readings to create controlled blood pressure variations. Machine learning models, including Random Forest, Logistic Regression, Support Vector Classifier, and K-Neighbors, were applied to predict blood pressure categories based on PTT and cardiovascular features. Results: Among the various machine learning models evaluated, Random Forest demonstrated effective performance, achieving an overall accuracy of 90%. The model also exhibited robustness, effectively handling the challenge of unbalanced classes, with a 95% confidence interval (CI) for accuracy ranging from 80% to 95%. This indicates its reliability across different data splits despite the class imbalance. Notably, PTT derived from PPG emerged as a critical predictive feature, further enhancing the model’s ability to accurately classify blood pressure categories and solidifying its utility in non-invasive cardiovascular monitoring. Conclusions: The findings affirm the efficacy of using PTT measurements from PPG, IPG, and ECG as reliable predictors for non-invasive blood pressure monitoring. This study substantiates the integration of these techniques into wearable devices, offering a significant advancement for continuous, cuffless, and non-invasive blood pressure assessment. Full article