Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty

Bolam, Scott M.; Batinica, Bruno; Yeung, Ted; Weaver, Sebastian; Cantamessa, Astrid; Vanderboor, Teresa C.; Yeung, Shasha; Munro, Jacob T.; Fernandez, Justin; Besier, Thor F.; Monk, Paul

doi:10.3390/s21155143

Cited by 37 publications

(29 citation statements)

References 50 publications

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“…However, telemedicine-oriented patient education may well solve the problem [37,61,62]. Studies conducted for virtual consultations for orthopedics usually focus on new solutions and technologies [59,[63][64][65][66][67][68][69], patient and clinician satisfaction [4,24,26,46,49,[70][71][72][73][74][75][76][77], clinical outcome measures [78][79][80][81][82], and cost analysis of traditional versus teleconsultation [82][83][84][85][86][87].…”

Section: Discussionmentioning

confidence: 99%

Orthopedic Telemedicine Outpatient Practice Diagnoses Set during the First COVID-19 Pandemic Lockdown—Individual Observation

Glinkowski

2022

IJERPH

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The COVID-19 pandemic has caused a substantial intensification of the telemedicine transformation process in orthopedics since 2020. In the light of the legal regulations introduced in Poland, from the beginning of the SARS-CoV-2 pandemic, physicians, including orthopedic surgeons, have had the opportunity to conduct specialist teleconsultations. Teleconsultations increase epidemiological safety and significantly reduce the exposure of patients and medical staff to direct transmission of the viral vector and the spread of infections. The study aimed to describe diagnoses and clinical aspects of consecutive orthopedic teleconsultations (TC) during the pandemic lockdown. The diagnoses were set according to the International Classification of Diseases (ICD-10). Hybrid teleconsultations used smartphones and obligatory Electronic Health Record (EHR) with supplemental voice, SMS, MMS, Medical images, documents, and video conferencing if necessary. One hundred ninety-eight consecutive orthopedic teleconsultations were served for 615 women and 683 men (mean age 41.82 years ± 11.47 years). The most frequently diagnosed diseases were non-acute orthopedic disorders “M” (65.3%) and injuries “S” (26.3%). Back pain (M54) was the most frequent diagnosis (25.5%). Although virtual orthopedic consultation cannot replace an entire personal visit to a specialist orthopedic surgeon, in many cases, teleconsultation enables medical staff to continue to participate in providing medical services at a sufficiently high medical level to ensure patient and physician. The unified approach to TC diagnoses using ICD-10 or ICD-11 may improve further research on telemedicine-related orthopedics repeatability. Future research directions should address orthopedic teleconsultations’ practical aspects and highlight legal, organizational, and technological issues with their implementations.

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Section: Discussionmentioning

confidence: 99%

Orthopedic Telemedicine Outpatient Practice Diagnoses Set during the First COVID-19 Pandemic Lockdown—Individual Observation

Glinkowski

2022

IJERPH

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“…Bolam et al 46 undertook a pilot cohort study of 14 prospective patients undergoing primary knee arthroplasty for osteoarthritis (OA). Remote patient monitoring was performed in the community every week from the second to sixth postoperative weeks.…”

Section: Wearable and Smart Sensorsmentioning

confidence: 99%

Follow-up after arthroplasty surgery

Hansjee

Giebaly

Shaarani

et al. 2022

The Bone & Joint Journal

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We aim to explore the potential technologies for monitoring and assessment of patients undergoing arthroplasty by examining selected literature focusing on the technology currently available and reflecting on possible future development and application. The reviewed literature indicates a large variety of different hardware and software, widely available and used in a limited manner, to assess patients’ performance. There are extensive opportunities to enhance and integrate the systems which are already in existence to develop patient-specific pathways for rehabilitation. Cite this article: Bone Joint J 2022;104-B(10):1104–1109.

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“…The advent and development of wearable sensors over the last decade offers a natural alternative as a response to this criticism [2,2,[6][7][8]. In effect, they are lightweight and a lot less expensive than equipping an entire room with cameras and sensors to record every move [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…The main limitation of wearable sensors for monitoring gait in daily life situations is that the collected data does not contain only phases during which the subject is actually walking. To circumvent this issue, most gait monitoring solutions based on wearable sensors either collect data in laboratory [2,18] or in a semi free-living environment with instructions to keep walking during recording [7,8]. However, everyday life gait-monitoring solutions are key for studying pathologies such as Parkinson's disease in which gait is not impacted equally during all times of day.…”

Section: Introductionmentioning

confidence: 99%

A Novel Walking Activity Recognition Model for Rotation Time Series Collected by a Wearable Sensor in a Free-Living Environment

Brard

Bellanger

Chevreuil³

et al. 2022

Sensors

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Solutions to assess walking deficiencies are widespread and largely used in healthcare. Wearable sensors are particularly appealing, as they offer the possibility to monitor gait in everyday life, outside a facility in which the context of evaluation biases the measure. While some wearable sensors are powerful enough to integrate complex walking activity recognition models, non-invasive lightweight sensors do not always have the computing or memory capacity to run them. In this paper, we propose a walking activity recognition model that offers a viable solution to this problem for any wearable sensors that measure rotational motion of body parts. Specifically, the model was trained and tuned using data collected by a motion sensor in the form of a unit quaternion time series recording the hip rotation over time. This time series was then transformed into a real-valued time series of geodesic distances between consecutive quaternions. Moving average and moving standard deviation versions of this time series were fed to standard machine learning classification algorithms. To compare the different models, we used metrics to assess classification performance (precision and accuracy) while maintaining the detection prevalence at the level of the prevalence of walking activities in the data, as well as metrics to assess change point detection capability and computation time. Our results suggest that the walking activity recognition model with a decision tree classifier yields the best compromise in terms of precision and computation time. The sensor that was used had purposely low computing and memory capacity so that reported performances can be thought of as the lower bounds of what can be achieved. Walking activity recognition is performed online, i.e., on-the-fly, which further extends the range of applicability of our model to sensors with very low memory capacity.

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Remote Patient Monitoring with Wearable Sensors Following Knee Arthroplasty

Cited by 37 publications

References 50 publications

Orthopedic Telemedicine Outpatient Practice Diagnoses Set during the First COVID-19 Pandemic Lockdown—Individual Observation

Orthopedic Telemedicine Outpatient Practice Diagnoses Set during the First COVID-19 Pandemic Lockdown—Individual Observation

Follow-up after arthroplasty surgery

A Novel Walking Activity Recognition Model for Rotation Time Series Collected by a Wearable Sensor in a Free-Living Environment

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