Measurement of Heart Rate Using the Withings ScanWatch Device during Free-living Activities : Validation Study

Funding Information: This research is part of the Eastern Corridor Medical Engineering (ECME) project, which has been funded by European Union’s INTERREG VA programme, managed by the Special EU Programmes Body (SEUPB).Peer reviewedPublisher PD

Does Connected Health Technology Improve Health-Related Outcomes in Rural Cardiac Populations? Systematic Review Narrative Synthesis

Individuals living in rural areas are more likely to experience cardiovascular diseases (CVD) and have increased barriers to regular physical activity in comparison to those in urban areas. This systematic review aimed to understand the types and effects of home-based connected health technologies, used by individuals living in rural areas with CVD. The inclusion criteria included technology deployed at the participant’s home and could be an mHealth (smart device, fitness tracker or app) or telehealth intervention. Nine electronic databases were searched across the date range January 1990–June 2021. A total of 207 full texts were screened, of which five studies were included, consisting of 603 participants. Of the five studies, four used a telehealth intervention and one used a form of wearable technology. All interventions which used a form of telehealth found a reduction in overall healthcare utilisation, and one study found improvements in CVD risk factors. Acceptability of the technologies was mixed, in some studies barriers and challenges were cited. Based on the findings, there is great potential for implementing connected health technologies, but due to the low number of studies which met the inclusion criteria, further research is required within rural areas for those living with cardiovascular disease

Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study

Background: Accurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities.Objective: The primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise.Methods: A total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error.Results: Overall, there was a very good correlation between the Polar OH1 and Polar H10 devices (r=0.95), with a mean bias of −1 beats·min-1 and limits of agreement of −20 to 19 beats·min-1. The Fitbit Charge 3 device underestimated heart rate by 7 beats·min-1 compared with Polar H10, with a limit of agreement of −46 to 33 beats·min-1 and poor correlation (r=0.8). The mean absolute percentage error for both devices was deemed acceptable

Physical Activity Monitoring in Patients with Neurological Disorders: A Review of Novel Body-Worn Devices

Aim: The aim was to conduct a systematic review to examine the literature reporting the validityand reliability of wearable physical activity monitoring in individuals with neurologicaldisorders. Method: A systematic search of the literature was performed using a specific searchstrategy in PubMed and CINAHL. A search constraint of articles published in English, includinghuman participants, published between January 2008 and March 2017 was applied. Peerreviewedstudies which enrolled adult participants with any neurological disorder were included.For the studies which sought to explore the validity of activity monitors, the outcomesmeasured using the monitor were compared to a criterion measure of physical activity. Thestudies methodological quality was assessed using an adapted version of the Quality Assessmentof Diagnostic Accuracy Studies (QUADAS) framework. Data extracted from each studyincluded the following: characteristics of the study participants, study setting, devices used,study protocol/methods, outcomes measured, and the validity/reliability of measurementproduced. Results: Twenty-three studies examining the validity and reliability of 16 differentmonitors were included. The identified studies comprised participants with a range of differentdisorders of neurological origin. The available evidence suggests that biaxial or triaxialaccelerometer devices positioned around the ankle produce the most accurate step countmeasurements in patients with neurological disorders. The findings regarding the reliabilityand validity of activity counts and energy expenditure are largely inconclusive in this population.Discussion: Ankle-worn biaxial or triaxial accelerometer-type devices provide the mostaccurate measurement of physical activity. However, further work is required in this field before wearable activity monitoring can be more widely implemented clinically. Standardisedactivity monitoring protocols are required for implementing these devices in clinical trials andclinical practice, and consensus is required as to the reporting and interpretation of derivedvariablesScience Foundation Irelan

Neuromuscular electrical stimulation in the treatment of knee osteoarthritis: a systematic review and meta-analysis

Objective: To assess the effectiveness of surface neuromuscular electrical stimulation in the treatment of knee osteoarthritis. Design: Systematic review and meta-analysis of randomized controlled and controlled clinical trials Methods: Studies were identified from databases (MEDLINE, EMBASE, CINAHL, Sports Discus, PEDro and the Cochrane Library) searched to January 2011 using a battery of keywords. Two reviewers selected studies meeting inclusion criteria. The methodological quality of the included studies was assessed using the Thomas Test and the strength of the evidence was then graded using the Agency for Health Care Policy and Research guidelines. Data were pooled and meta-analyses were performed. Results: Nine randomized controlled trials and one controlled clinical trial, studying a total of 409 participants (n = 395 for randomized controlled trials, and n = 14 for controlled trial) with a diagnosis of osteoarthritis were included. Inconsistent evidence (level D) was found that neuromuscular electrical stimulation has a significant impact on measures of pain, function and quadriceps femoris muscle strength in knee osteoarthritis. Conclusion: The role of neuromuscular electrical stimulation in the treatment of knee osteoarthritis is ambiguous. Therefore, future work is needed in this field to clearly establish the role of neuromuscular electrical stimulation in this population

The Use of Inertial Sensors for the Classification of Rehabilitation Exercises

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, Illinois, United States of America, 26-30 August 2014The benefits of exercise in rehabilitation after orthopaedic surgery or following a musculoskeletal injury has been widely established. Within a hospital or clinical environment, adherence levels to rehabilitation exercise programs are high due to the supervision of the patient during the rehabilitation process. However, adherence levels drop significantly when patients are asked to perform the program at home. This paper describes the use of simple inertial sensors for the purpose of developing a biofeedback system to monitor adherence to rehabilitation programs. The results show that a single sensor can accurately distinguish between seven commonly prescribed rehabilitation exercises with accuracies between 93% and 95%. Results also show that the use of multiple sensor units does not significantly improve results therefore suggesting that a single sensor unit can be used as an input to an exercise biofeedback system

Rehabilitation exercise assessment using inertial sensors: a cross-sectional analytical study

Background: Accurate assessments of adherence and exercise performance are required in order to ensure that patients adhere to and perform their rehabilitation exercises correctly within the home environment. Inertial sensors have previously been advocated as a means of achieving these requirements, by using them as an input to an exercise biofeedback system. This research sought to investigate whether inertial sensors, and in particular a single sensor, can accurately classify exercise performance in patients performing lower limb exercises for rehabilitation purposes. Methods:Fifty-eight participants (19 male, 39 female, age: 53.9 +/- 8.5 years, height: 1.69 +/- 0.08 m, weight: 74.3 +/- 13.0 kg) performed ten repetitions of seven lower limb exercises (hip abduction, hip flexion, hip extension, knee extension, heel slide, straight leg raise, and inner range quadriceps). Three inertial sensor units, secured to the thigh, shin and foot of the leg being exercised, were used to acquire data during each exercise. Machine learning classification methods were applied to quantify the acquired data. Results:The classification methods achieved relatively high accuracy at distinguishing between correct and incorrect performance of an exercise using three, two, or one sensor while moderate efficacy scores were also achieved by the classifier when attempting to classify the particular error in exercise performance. Results also illustrated that a reduction in the number of inertial sensor units employed has little effect on the overall efficacy results. Conclusion:The results revealed that it is possible to classify lower limb exercise performance using inertial sensors with satisfactory levels of accuracy and reducing the number of sensors employed does not reduce the accuracy of the methodScience Foundation Irelan

Towards fully instrumented and automated assessment of motor function tests

2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Nevada, United States of America, 4-7 MarchQuantitative assessment of mobility and motor function is critical to our understanding and treatment of musculoskeletal and neurological diseases. Instrumented tests augment traditional approaches by moving from a single, often subjective, performance metric to multiple objective measures. In this study, we investigated ways of automatically capturing motor performance by leveraging data from a network of six wearable sensors worn at five different locations by 17 healthy volunteers while performing a battery of motor function tests. We developed a framework to segment motor tasks, e.g. walking and standing up, from 3D acceleration and angular velocity data, and extracted features. Results were compared to clinical test scores and manual annotations of the data. For the best performing sensors, we achieved a rate of correct classification of 82 to 100% and mean temporal accuracy of 0.1 to 0.6 s. We provided guidelines on sensor placement to maximize accuracy of the motor assessment, and a better interpretation of the data using our unsupervised subject-specific approach