scholarly journals Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5143
Author(s):  
Scott M. Bolam ◽  
Bruno Batinica ◽  
Ted C. Yeung ◽  
Sebastian Weaver ◽  
Astrid Cantamessa ◽  
...  
Keyword(s):  
Range Of Motion ◽  
Knee Arthroplasty ◽  
Patient Monitoring ◽  
Impact Load ◽  
Flexion Angle ◽  
Remote Patient Monitoring ◽  
Cumulative Impact ◽  
Load Asymmetry ◽  
The Mean ◽  
Remote Patient

(Background) Inertial Measurement Units (IMUs) provide a low-cost, portable solution to obtain functional measures similar to those captured with three-dimensional gait analysis, including spatiotemporal gait characteristics. The primary aim of this study was to determine the feasibility of a remote patient monitoring (RPM) workflow using ankle-worn IMUs measuring impact load, limb impact load asymmetry and knee range of motion in combination with patient-reported outcome measures. (Methods) A pilot cohort of 14 patients undergoing primary knee arthroplasty for osteoarthritis was prospectively enrolled. RPM in the community was performed weekly from 2 up to 6 weeks post-operatively using wearable IMUs. The following data were collected using IMUs: mobility (Bone Stimulus and cumulative impact load), impact load asymmetry and maximum knee flexion angle. In addition, scores from the Oxford Knee Score (OKS), EuroQol Five-dimension (EQ-5D) with EuroQol visual analogue scale (EQ-VAS) and 6 Minute Walk Test were collected. (Results) On average, the Bone Stimulus and cumulative impact load improved 52% (p = 0.002) and 371% (p = 0.035), compared to Post-Op Week 2. The impact load asymmetry value trended (p = 0.372) towards equal impact loading between the operative and non-operative limb. The mean maximum flexion angle achieved was 99.25° at Post-Operative Week 6, but this was not significantly different from pre-operative measurements (p = 0.1563). There were significant improvements in the mean EQ-5D (0.20; p = 0.047) and OKS (10.86; p < 0.001) scores both by 6 weeks after surgery, compared to pre-operative scores. (Conclusions) This pilot study demonstrates the feasibility of a reliable and low-maintenance workflow system to remotely monitor post-operative progress in knee arthroplasty patients. Preliminary data indicate IMU outputs relating to mobility, impact load asymmetry and range of motion can be obtained using commercially available IMU sensors. Further studies are required to directly correlate the IMU sensor outputs with patient outcomes to establish clinical significance.

Remote Patient Monitoring Using Mobile Health for Total Knee Arthroplasty: Validation of a Wearable and Machine Learning–Based Surveillance Platform

2019 ◽  
Vol 34 (10) ◽  
pp. 2253-2259 ◽  
Author(s):  
Prem N. Ramkumar ◽  
Heather S. Haeberle ◽  
Deepak Ramanathan ◽  
William A. Cantrell ◽  
Sergio M. Navarro ◽  
...  
Keyword(s):  
Machine Learning ◽  
Total Knee Arthroplasty ◽  
Mobile Health ◽  
Knee Arthroplasty ◽  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Total Knee ◽  
Remote Patient

scholarly journals Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 776
Author(s):  
Xiaohui Tao ◽  
Thanveer Basha Shaik ◽  
Niall Higgins ◽  
Raj Gururajan ◽  
Xujuan Zhou
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Radio Frequency Identification ◽  
Patient Monitoring ◽  
Vital Signs ◽  
Remote Patient Monitoring ◽  
Rfid Technology ◽  
Rpm System ◽  
Frequency Identification ◽  
Remote Patient

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader–antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.

Leadless and Wireless Cardiac Devices: The Next Frontier in Remote Patient Monitoring

2021 ◽  
Vol 46 (5) ◽  
pp. 100800
Author(s):  
Abdulaziz Joury ◽  
Tamunoinemi Bob-Manuel ◽  
Alexandra Sanchez ◽  
Fnu Srinithya ◽  
Amber Sleem ◽  
...  
Keyword(s):  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Cardiac Devices ◽  
Remote Patient

scholarly journals Home physiotherapy with vs. without supervision of physiotherapist for assessing manipulation under anaesthesia after total knee arthroplasty

Arthroplasty ◽  
2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Sanjay Bhalchandra Londhe ◽  
Ravi Vinod Shah ◽  
Amit Pankaj Doshi ◽  
Shubhankar Sanjay Londhe ◽  
Kavita Subhedar ◽  
...  
Keyword(s):  
Total Knee Arthroplasty ◽  
Range Of Motion ◽  
Knee Arthroplasty ◽  
Forgotten Joint Score ◽  
Group A ◽  
Manipulation Under Anaesthesia ◽  
Total Knee ◽  
The Mean ◽  
Group B ◽  
Discharge From Hospital

Abstract The aim of this retrospective cohort study was to compare home physiotherapy with or without supervision of physiotherapist for assessing manipulation under anaesthesia after total knee arthroplasty. Methods A total of 900 patients (including 810 females and 90 males) who had undergone total knee arthroplasty were divided into group A (n = 300) and group B (n = 600). Patients in group A had home physiotherapy on their own after discharge from hospital. The physiotherapist did not visit them at home. Patients in group B received home physiotherapy under supervision of physiotherapist for 6 weeks after discharge from hospital. Patients’ age, range of motion of the knee, and forgotten joint score-12 were assessed. A p < 0.05 was considered statistically significant. Results In group A, the mean age was 69.1 ± 14.3 years (range: 58 to 82 years); in group B, the mean age was 66.5 ± 15.7 years (range: 56 to 83 years) (p > 0.05). Preoperatively, the mean range of motion of the knee in group A and B was 95.8° ± 18.1° and 95.4° ± 17.8°, respectively (p > 0.05). The mean forgotten joint score-12 of group A and B were 11.90 ± 11.3 and 11.72 ± 12.1 (p > 0.05), respectively. Six weeks after total knee arthroplasty, the mean ROM of the knee in group A and B was 109.7° ± 22.3° and 121° ± 21.5°, respectively (p < 0.05). The mean postoperative forgotten joint score-12 of the group A and B was 24.5 ± 16.4 and 25.6 ± 17.4, respectively (p > 0.05). The rate of manipulation under anaesthesia was 3% in group A and 0.2% in group B (p < 0.05). Conclusion After total knee arthroplasty, frequent physiotherapist’s instruction helps the patients improve knee exercises and therefore decrease the risk of revision surgery. The home physiotherapy under supervision of physiotherapist lowers the rate of manipulation under anaesthesia. Level of evidence Therapeutic study, Level IIa.

scholarly journals Effect of Posterior Tibial Slope Change on Postoperative Range of Motion and Clinical Outcomes after Posterior Cruciate-Substituting Total Knee Arthroplasty

2021 ◽  
Author(s):  
O-Sung Lee ◽  
Jangyun Lee ◽  
Myung Chul Lee ◽  
Hyuk-Soo Han
Keyword(s):  
Total Knee Arthroplasty ◽  
Range Of Motion ◽  
Correlation Coefficient ◽  
Knee Arthroplasty ◽  
Tibial Slope ◽  
Posterior Tibial Slope ◽  
Posterior Tibial ◽  
Clinical Scores ◽  
Total Knee ◽  
The Mean

AbstractThe posterior tibial slope (PTS) is usually adjusted by less than 5 degrees, without considering its individual difference, during posterior cruciate-substituting (PS) total knee arthroplasty (TKA). The effect of these individual changes of PTS would be important because clinical results depending on postoperative PTS were reported conflictingly. We investigated the effect of the change in PTS on the postoperative range of motion (ROM) and clinical scores after PS TKA. We retrospectively reviewed 164 knees from 107 patients who underwent PS TKA with a 2-year follow-up. We analyzed the preoperative and postoperative PTS, ROM, visual analog scale pain scale, Western Ontario and McMaster University Index (WOMAC), Hospital for Special Surgery Knee Score, Knee Society Score, and Forgotten Joint Score (FJS). The association of the absolute change in PTS with ROM and clinical scores was analyzed using correlation analysis and multiple regression analysis. As a result, the mean PTS and mean ROM changed from 9.6 ±  3.4 and 120.1 ±  15.4 degrees preoperatively to 2.0 ±  1.3 and 128.4 ±  9.3 degrees postoperatively, and the mean PTS change was 7.6 ±  3.5 degrees. The PTS change had no statistically significant association with the postoperative ROM and clinical scoring systems, although it did have a weak positive correlation with WOMAC function, No 10 (difficulty in rising from sitting) (correlation coefficient = 0.342, p = 0.041), and moderate positive correlation with the FJS, No. 6 (awareness when climbing stairs) (correlation coefficient = 0.470, p = 0.001). The authors concluded that the amount of change in PTS did not affect the postoperative ROM and clinical scores, although proximal tibial resection with a constant target of PTS resulted in individually different changes in the PTS after PS TKA,

scholarly journals Emerging Role of Remote Patient Monitoring in Pulmonary Care

CHEST Journal ◽  
2021 ◽  
Vol 159 (2) ◽  
pp. 477-478
Author(s):  
Neeraj R. Desai ◽  
Edward J. Diamond
Keyword(s):  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Remote Patient
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