Quantifying lumbar mobility using a single tri-axial accelerometer.

Background: Lumbar mobility is regarded as important for assessing and managing low back pain (LBP). Inertial Measurement Units (IMUs) are currently the most feasible technology for quantifying lumbar mobility in clinical and research settings. However, their gyroscopes are susceptible to drift errors, limiting their use for long-term remote monitoring. Research question: Can a single tri-axial accelerometer provide an accurate and feasible alternative to a multi-sensor IMU for quantifying lumbar flexion mobility and velocity? Methods: In this cross-sectional study, 18 healthy adults performed nine repetitions of full spinal flexion movements. Lumbar flexion mobility and velocity were quantified using a multi-sensor IMU and just the tri-axial accelerometer within the IMU. Correlations between the two methods were assessed for each percentile of the lumbar flexion movement cycle, and differences in measurements were modelled using a Generalised Additive Model (GAM). Results: Very high correlations (r > 0.90) in flexion angles and velocities were found between the two methods for most of the movement cycle. However, the accelerometer overestimated lumbar flexion angle at the start (-4.7° [95 % CI -7.6° to -1.8°]) and end (-4.8° [95 % CI -7.7° to -1.9°]) of movement cycles, but underestimated angles (maximal difference of 4.3° [95 % CI 1.4° to 7.2°]) between 7 % and 92 % of the movement cycle. For flexion velocity, the accelerometer underestimated at the start (16.6°/s [95%CI 16.0 to 17.2°/s]) and overestimated (-12.3°/s [95%CI -12.9 to -11.7°/s]) at the end of the movement, compared to the IMU. Significance: Despite the observed differences, the study suggests that a single tri-axial accelerometer could be a feasible tool for continuous remote monitoring of lumbar mobility and velocity. This finding has potential implications for the management of LBP, enabling more accessible and cost-effective monitoring of lumbar mobility in both clinical and research settings.

Device-measured sedentary time and intensity-specific physical activity in relation to all-cause and cardiovascular disease mortality: the UK Biobank cohort study.

BACKGROUND AND AIMS: Understanding the amounts of intensity-specific movement needed to attenuate the association between sedentary time and mortality may help to inform personalized prescription and behavioral counselling. Herein, we examined the joint associations of sedentary time and intensity-specific physical activity with all-cause and cardiovascular disease (CVD) mortality. METHODS: Prospective cohort study including 73,729 adults from the UK Biobank who wore an Axivity AX3 accelerometer on their dominant wrist for at least 3 days, being one a weekend day, between June 2013 and December 2015. We considered the median tertile values of sedentary time and physical activity in each intensity band to determine the amount of physical activity needed to attenuate the association between sedentary time and mortality. RESULTS: During a median of 6.9 years of follow-up (628,807 person-years), we documented 1521 deaths, including 388 from CVD. Physical activity of any intensity attenuated the detrimental association of sedentary time with mortality. Overall, at least a median of 6 min/day of vigorous physical activity, 30 min/day of MVPA, 64 min/day of moderate physical activity, or 163 min/day of light physical activity (mutually-adjusted for other intensities) attenuated the association between sedentary time and mortality. High sedentary time was associated with higher risk of CVD mortality only among participants with low MVPA (HR 1.96; 95% CI 1.23 to 3.14). CONCLUSIONS: Different amounts of each physical activity intensity may attenuate the association between high sedentary time and mortality.

Joint associations of diet and physical activity with incident type 2 diabetes and hypertension: an analysis of 144,288 UK Biobank participants.

BACKGROUND: Studies examining the joint associations of lifestyle exposures can reveal novel synergistic and joint effects, but no study has examined the joint association of diet and physical activity (PA) with type 2 diabetes (T2D) and hypertension. The aim of this study is to examine the joint associations of PA and diet with incidence of type T2D and hypertension, as a combined outcome and separately in a large sample of UK adults. METHODS: This prospective cohort study included 144,288 UK Biobank participants aged 40-69. Moderate to vigorous PA (MVPA) was measured using the International Physical Activity Questionnaire and a wrist accelerometer. We categorised PA and diet indicators (diet quality score (DQS) and energy intake (EI)) based on tertiles and derived joint PA and diet variables. Outcome was major cardiometabolic disease incidence (combination of T2D and hypertension). RESULTS: A total of 14,003(7.1%) participants developed T2D, 28,075(19.2%) developed hypertension, and 30,529(21.2%) developed T2D or hypertension over a mean follow-up of 10.9(3.7) years. Participants with middle and high self-reported MVPA levels had lower risk of major cardiometabolic disease regardless of diet, e.g. among high DQS group, hazard ratios in middle and high MVPA group were 0.90 (95%CI:0.86-0.94), and 0.88(95%CI:0.84-0.92), respectively. Participants with jointly high device-measured MVPA and high DQS levels had lower major cardiometabolic disease risk (HR: 0.84, 95%CI:0.71-0.99). The equivalent joint device-measured MVPA and EI exposure analyses showed no clear pattern of associations with the outcomes. CONCLUSION: Higher PA is an important component in cardiometabolic disease prevention across all diet quality and total EI groups. The observed lack of association between diet health outcomes may stem from a lower DQS.

Patterns of physical activity of people with COPD during participation in a pulmonary rehabilitation program.

INTRODUCTION: Very few studies have examined patterns of physical activity (PA) during a pulmonary rehabilitation (PR) program in people with COPD. AIMS: To compare the patterns of PA in: 1) the week before commencing PR (pre-PR) with a week during PR (PR week); 2) PR days and non-PR days during a PR week; 3) pre-PR and the week following PR completion (post PR). METHODS: This was a multicenter, prospective cohort study. Participants attended twice weekly supervised PR for 8-12 weeks. Daily step count (primary outcome), time in light activities, time in moderate to vigorous PA (MVPA), total sedentary time and sit-to-stand (STS) transitions were measured using a thigh worn accelerometer for seven days, at each assessment time point: pre-PR, PR week and post PR. RESULTS: 29 participants, mean age (SD) 69years(7), FEV1 53%pred(16). The PR week compared to pre-PR, showed higher daily: step count (mean difference (95%CI)), 941steps(388-1494); and MVPA, 11mins(6-15), with no difference in: time in light activities, -1min(-6-5); total sedentary time, 7mins(-21-36); or STS transitions, 0(-5-6). PR days compared to non-PR days showed higher: step count, 2810steps(1706-3913); time in light activities 11mins(1-20); time in MVPA, 27mins(17-35) and STS transitions, 8(4-12), with no difference in total sedentary time: -33mins(-80-15). There were no differences in any PA measures post-PR compared to pre-PR (p<0.05). CONCLUSION: Daily step count and time spent in MVPA increased significantly during the PR week, solely due to increased PA on days participants attended PR.

Association between profiles of accelerometer-measured daily movement behaviour and mortality risk: a prospective cohort study of British older adults.

Objectives: We identified profiles of wake-time movement behaviours (sedentary behaviours, light intensity physical activity and moderate-to-vigorous physical activity) based on accelerometer-derived features among older adults and then examined their association with all-cause mortality. Methods: Data were drawn from a prospective cohort of 3991 Whitehall II accelerometer substudy participants aged 60-83 years in 2012-2013. Daily movement behaviour profiles were identified using k-means cluster analysis based on 13 accelerometer-assessed features characterising total duration, frequency, bout duration, timing and activity intensity distribution of movement behaviour. Cox regression models were used to assess the association between derived profiles and mortality risk. Results: Over a mean follow-up of 8.1 (SD 1.3) years, a total of 410 deaths were recorded. Five distinct profiles were identified and labelled as 'active' (healthiest), 'active sitters', 'light movers', 'prolonged sitters', and 'most sedentary' (most deleterious). In model adjusted for sociodemographic, lifestyle, and health-related factors, compared with the 'active' profile, 'active sitters' (HR 1.57, 95% CI 1.01 to 2.44), 'light movers' (HR 1.75, 95% CI 1.17 to 2.63), 'prolonged sitters' (HR 1.67, 95% CI 1.11 to 2.51), 'most sedentary' (HR 3.25, 95% CI 2.10 to 5.02) profiles were all associated with a higher risk of mortality. Conclusion: Given the threefold higher mortality risk among those with a 'most sedentary' profile, public health interventions may target this group wherein any improvement in physical activity and sedentary behaviour might be beneficial.

Association of physical activity patterns with nocturnal hypoglycemia events in youth with type 1 diabetes.

AIMS: This study sought to elucidate the interactions among physical activity (PA) patterns, mean glucose concentrations, and the incidence of nocturnal hypoglycemia events in children and adolescents with type 1 diabetes, examining the moderating influence of daily dosage on these associations. MATERIAL AND METHODS: Eighty-two participants aged 6 to 18 years (43.9% girls) from the Diactive-1 Cohort Study, diagnosed with type 1 diabetes, were included. Data collection involved continuous glucose monitoring, accelerometry to assess real-world PA, as well as documentation of daily insulin doses and carbohydrate counting over the same seven days. RESULTS: A total of 19 participants experienced at least one nocturnal hypoglycemia event over a span of 574 measurement days (106 days with and 451 days without nocturnal hypoglycemia). Higher levels of vigorous PA (VPA) were associated with lower same-day mean glucose levels (p = 0.014). Additionally, higher levels of moderate PA (p = 0.023), VPA (p = 0.011), and moderate-to-vigorous PA (p = 0.010) were associated with a greater number of nocturnal hypoglycemia events. Specifically, a significant association was identified between VPA and nocturnal hypoglycemia events when the daily insulin dose were at or above 1.04 units per kilogram of body weight per day (p = 0.016). CONCLUSIONS: Daily VPA is associated with glucose reductions, potentially leading to more hypoglycemic episodes, particularly when there's an excess of daily insulin. This highlights the need for careful insulin management in children and adolescents with type 1 diabetes engaging in VPA.

Recognition of TaeKwonDo kicking techniques based on accelerometer sensors.

TaeKwonDo (TKD) is a worldwide sport in both competitive among athletes and physical exercise among the public scenarios. Measuring TKD kicks have been studied a lot in a laboratory setting but rarely in a free-living situation. Machine learning algorithm combined with accelerometer data was used to study some martial art styles, e.g., Chinese KungFu but little in TKD. The purpose of this study was to discover a method to recognize different kicking techniques in TKD. A total of 20 participants (35 % male) were recruited to perform front kick, roundhouse kick, side kick and back kick 6 times on each side with three accelerometers wore on waist, right ankle and left ankle. SVM and decision tree were used to analyze data and classify kicking movements. The usage of different combination of accelerometers were also compared. The result showed that using accelerometers on waist and both ankles, on waist and only right ankle, on only waist and combined with SVM model could have at least 0.96 accuracy of classification, while decision tree had the accuracies around 0.8. It was concluded that using SVM model on only waist data is the optimal choice because of the high accuracy and less accelerometers used.

Physical Activity Levels and Body Mass Index in Sport Education. Is There a Difference?

Purpose: The goals of this study were: (1) to assess students' physical activity levels in a sport education season according to the phases of the model, adjusted for body mass index; (2) to uncover the contribution of the phases of the model to the World Health Organization recommendations; (3) to understand its impact in students with overweight/obesity. Methods: A total of 42 primary education students with a mean age of 10.68 ± 0.69 years, enrolled in one year 5 (10-11 years) and one year 6 (11-12 years). Physical Education lessons of the same school agreed to participate. Students in both groups experienced a 14-lesson learning unit in team handball through the sport education. Each participant wore an ActiGraph GT3X accelerometer to measure physical activity levels, counts/minute and steps counted. Cole and Lobstein cutoff points were used to determine groups based on body mass index (thin, normal-weight, overweight/obese). Results: The results showed that the overweight/obese group achieved scores for moderate to vigorous physical activity and sedentary time that were not significantly different from the normal-weight group. According to the phases, the preseason was the most active and contributed most to the World Health Organization recommendations in all groups. Conclusions: Sport education could be considered an appropriate pedagogical framework to help overweight/obese children achieve moderate-to-vigorous physical activity and sedentary scores similar to their normal-weight classmates. Key elements of sport education include performing roles, learning work routines, and having the autonomy to choose games/tasks, all of which promote physical activity amongst all students.

Comparing national device-based physical activity surveillance systems: a systematic review.

BACKGROUND: Physical activity surveillance systems are important for public health monitoring but rely mostly on self-report measurement of physical activity. Integration of device-based measurements in such systems can improve population estimates, however this is still relatively uncommon in existing surveillance systems. This systematic review aims to create an overview of the methodology used in existing device-based national PA surveillance systems. METHODS: Four literature databases (PubMed, Embase.com, SPORTDiscus and Web of Science) were searched, supplemented with backward tracking. Articles were included if they reported on population-based (inter)national surveillance systems measuring PA, sedentary time and/or adherence to PA guidelines. When available and in English, the methodological reports of the identified surveillance studies were also included for data extraction. RESULTS: This systematic literature search followed the PRISMA guidelines and yielded 34 articles and an additional 18 methodological reports, reporting on 28 studies, which in turn reported on one or multiple waves of 15 different national and 1 international surveillance system. The included studies showed substantial variation between (waves of) systems in number of participants, response rates, population representativeness and recruitment. In contrast, the methods were similar on data reduction definitions (e.g. minimal number of valid days, non-wear time and necessary wear time for a valid day). CONCLUSIONS: The results of this review indicate that few countries use device-based PA measurement in their surveillance system. The employed methodology is diverse, which hampers comparability between countries and calls for more standardized methods as well as standardized reporting on these methods. The results from this review can help inform the integration of device-based PA measurement in (inter)national surveillance systems.

Total knee replacement with an accelerometer-based, hand-held navigation system improves knee alignment: reliable in all patients.

BACKGROUND: Achieving adequate alignment has traditionally been an important goal in total knee arthroplasty to achieve long-term implant survival. While accelerometer-based hand-held navigation systems (ABN) has been introduced as a way to achieve alignment, there is a limited body of evidence on its accuracy, especially in patients under 65 years with differing etiologies for knee arthritis. This study aimed to assess the precision of a specific ABN system in restoring the mechanical axis and report surgical variables and complications, with particular attention to younger patients. METHODS: We conducted a retrospective review of 310 primary TKA performed with ABN from May 2016 to February 2021. The mean patient age was 67.4 (SD 8.9) years, with 43% under 65 years and mean body mass index of 33.2 (SD 6.8). The average surgical time was 96.8 min (57-171) and the average follow-up was 3.3 years (1.9-6.7). Data regarding length of stay, pain, range of motion (ROM), complications, and reinterventions were collected from the institutional joint arthroplasty registry and the medical records. Preoperative mechanical axis measurements and postoperative radiological data, including mechanical axis, component alignment and mechanical alignment outliers were analyzed. RESULTS: The mean preoperative mechanical axis was 175.4° (SD 7.6), with 248 knees (80%) in preoperative varus. The mean postoperative mechanical axis was 179.5° (SD 1.96) with 98% of knees falling within ± 3° of the neutral mechanical axis. Only 6 knees (2 varus, 4 valgus) fell outside the ± 3° range. And 3 knees (1 varus, 2 valgus) fell outside the ± 5° range. In the sagittal plane, 296 knees (95.5%) knees were within ± 3° of goal of 3 degrees of femoral flexion and 302 (97.4%) knees were within ± 2° of goal 1° of slope for tibial component. Far outliers (alignment outside ± 5° of targeted position) were found in 3 knees. Factors such as posttraumatic arthrosis, previous surgery, presence of retained hardware, and age below 65 years were not associated with increase in alignment outliers and far outliers. No complications related to the navigation system were observed. There were 22 complications and 20 reoperations, including 2 revisions for periprosthetic joint infection and 1 revision for flexion instability. Patients that required knee manipulation achieved an ultimate flexion of 110° (SD 14.1). CONCLUSIONS: The ABN system proved to be user-friendly and accurate in reducing alignment outliers in both coronal and sagittal planes in all patient populations. It offers a straightforward navigation solution while preserving surgeon autonomy and the use of traditional surgical tools. These findings advocate for the integration of this navigation system as a valuable tool to enhance the precision of TKA surgery in all patient groups.

Can weekend catch-up sleep decrease the risk of cognitive dysfunction in older adults?

PURPOSE: This study investigated whether weekend catch-up sleep was related to a decreased risk of cognitive dysfunction in older Taiwanese adults by using self-reported diaries and objective accelerometer measurements. METHODS: This cross-sectional study enrolled participants who were aged ≥ 65 years and had the capability to walk independently from a medical center in Taipei City, Taiwan, between September 2020 and December 2022. Self-reported sleep diaries and tri-axial accelerometers were used to record and measure sleep-related data for 7 consecutive nights. Weekend catch-up sleep was defined as the mean of weekend sleep time minus the mean of weekdays sleep time. Mini-Mental State Examination (MMSE) was evaluated the risk of cognitive dysfunction. The association between weekend catch-up sleep and the MMSE score was examined using a binary logistic regression model. RESULTS: A total of 215 older adults (53.0% female; 80.5 ± 7.1 years old; 11.6% at risk of cognitive dysfunction) were included. In the adjusted model (adjusted for sex, education level, moderate-to-vigorous physical activity and total accelerometer wear time), both the self-reported sleep diaries (odds ratio [OR] = 0.26, 95% confidence interval [CI] = 0.09-0.69, P = 0.007) and the accelerometer data (OR = 0.27, 95% CI = 0.10-0.70, P = 0.007) indicated that weekend catch-up sleep could decrease the risk of cognitive dysfunction by 73-74%. CONCLUSION: The study findings suggest that there is an association between weekend catch-up sleep and lower risk for cognitive decline. The causal relationship between weekend catch-up sleep and cognitive function in older adults should be further investigated in a study with longitudinal design.

Continuous mobile measurement of camptocormia angle using four accelerometers.

Camptocormia, a severe flexion deformity of the spine, presents challenges in monitoring its progression outside laboratory settings. This study introduces a customized method utilizing four inertial measurement unit (IMU) sensors for continuous recording of the camptocormia angle (CA), incorporating both the consensual malleolus and perpendicular assessment methods. The setup is wearable and mobile and allows measurements outside the laboratory environment. The practicality for measuring CA across various activities is evaluated for both the malleolus and perpendicular method in a mimicked Parkinson disease posture. Multiple activities are performed by a healthy volunteer. Measurements are compared against a camera-based reference system. Results show an overall root mean squared error (RMSE) of 4.13° for the malleolus method and 2.71° for the perpendicular method. Furthermore, patient-specific calibration during the standing still with forward lean activity significantly reduced the RMSE to 2.45° and 1.68° respectively. This study presents a novel approach to continuous CA monitoring outside the laboratory setting. The proposed system is suitable as a tool for monitoring the progression of camptocormia and for the first time implements the malleolus method with IMU. It holds promise for effectively monitoring camptocormia at home.

A Method of Precise Auto-Calibration in a Micro-Electro-Mechanical System Accelerometer.

A novel design of a MEMS (Micro-Electromechanical System) capacitive accelerometer fabricated by surface micromachining, with a structure enabling precise auto-calibration during operation, is presented. Precise auto-calibration was introduced to ensure more accurate acceleration measurements compared to standard designs. The standard mechanical structure of the accelerometer (seismic mass integrated with elastic suspension and movable plates coupled with fixed plates forming a system of differential sensing capacitors) was equipped with three movable detection electrodes coupled with three fixed electrodes, thus creating three atypical tunneling displacement transducers detecting three specific positions of seismic mass with high precision, enabling the auto-calibration of the accelerometer while it was being operated. Auto-calibration is carried out by recording the accelerometer indication while the seismic mass occupies a specific position, which corresponds to a known value of acting acceleration determined in a pre-calibration process. The diagram and the design of the mechanical structure of the accelerometer, the block diagram of the electronic circuits, and the mathematical relationships used for auto-calibration are presented. The results of the simulation studies related to mechanical and electric phenomena are discussed.

A Ground-Based Electrostatically Suspended Accelerometer.

In this study, we have developed an electrostatically suspended accelerometer (ESA) specifically designed for ground use. To ensure sufficient overload capacity and minimize noise resulting from high suspension voltage, we introduced a proof mass design featuring a hollow, thin-walled cylinder with a thin flange fixed at the center, offering the highest surface-area-to-mass ratio compared to various typical proof mass structures. Preload voltage is directly applied to the proof mass via a golden wire, effectively reducing the maximum supply voltage for suspension. The arrangement of suspension electrodes, offering five degrees of freedom and minimizing cross-talk, was designed to prioritize simplicity and maximize the utilization of electrode area for suspension purposes. The displacement detection and electrostatic suspension force were accurately modeled based on the structure. A controller incorporating an inverse winding mechanism was developed and simulated using Simulink. The simulation results unequivocally demonstrate the successful completion of the stable initial levitation process and suspension under ±1g overload.

Helical Gearbox Defect Detection with Machine Learning Using Regular Mesh Components and Sidebands.

The current paper presents helical gearbox defect detection models built from raw vibration signals measured using a triaxial accelerometer. Gear faults, such as localized pitting, localized wear on helical pinion tooth flanks, and low lubricant level, are under observation for three rotating velocities of the actuator and three load levels at the speed reducer output. The emphasis is on the strong connection between the gear faults and the fundamental meshing frequency GMF, its harmonics, and the sidebands found in the vibration spectrum as an effect of the amplitude modulation (AM) and phase modulation (PM). Several sets of features representing powers on selected frequency bands or/and associated peak amplitudes from the vibration spectrum, and also, for comparison, time-domain and frequency-domain statistical feature sets, are proposed as predictors in the defect detection task. The best performing detection model, with a testing accuracy of 99.73%, is based on SVM (Support Vector Machine) with a cubic kernel, and the features used are the band powers associated with six GMF harmonics and two sideband pairs for all three accelerometer axes, regardless of the rotation velocities and the load levels.

Off-Design Operation and Cavitation Detection in Centrifugal Pumps Using Vibration and Motor Stator Current Analyses.

Centrifugal pumps are essential in many industrial processes. An accurate operation diagnosis of centrifugal pumps is crucial to ensure their reliable operation and extend their useful life. In real industry applications, many centrifugal pumps lack flowmeters and accurate pressure sensors, and therefore, it is not possible to determine whether the pump is operating near its best efficiency point (BEP). This paper investigates the detection of off-design operation and cavitation for centrifugal pumps with accelerometers and current sensors. To this end, a centrifugal pump was tested under off-design conditions and various levels of cavitation. A three-axis accelerometer and three Hall-effect current sensors were used to collect vibration and stator current signals simultaneously under each state. Both kinds of signals were evaluated for their effectiveness in operation diagnosis. Signal processing methods, including wavelet threshold function, variational mode decomposition (VMD), Park vector modulus transformation, and a marginal spectrum were introduced for feature extraction. Seven families of machine learning-based classification algorithms were evaluated for their performance when used for off-design and cavitation identification. The obtained results, using both types of signals, prove the effectiveness of both approaches and the advantages of combining them in achieving the most reliable operation diagnosis results for centrifugal pumps.

Is device-measured physical activity associated with musculoskeletal disorders among young adult Finnish men?

Background: Musculoskeletal (MSK) disorders represent a significant burden to society and can be unpleasant for the affected individuals. Physical activity (PA) can prevent MSK disorders while conferring other health benefits. The present study aimed to investigate associations between device-measured PA and perceived MSK disorders among young adult men. Methods: PA at different intensity levels, standing, and sedentary behavior were measured with a hip-worn accelerometer in a cohort of 422 young adult Finnish men aged 26 years on average. The incidences of three common MSK disorders (viz., knee pain, lumbar radicular pain, and lumbago pain) during the last month were inquired by a questionnaire. Binary logistic regression was used to examine the associations between the MSK outcomes and explanatory PA variables (PA times at different intensity levels, standing, and sedentary times). The models were controlled for age, education, smoking, BMI, and maximal oxygen uptake. Results: PA, standing, and sedentary times were not significantly associated with the incidence of perceived MSK pain during the last month, except for lumbago pain. Lumbago pain was slightly more probable if the time spent in light PA increased, even after controlling for potential confounding factors, including moderate-to-vigorous PA, with an odds ratio (OR) of 1.07 (95% CI: 1.02-1.14). Sedentary time showed an opposite association, with an OR of 0.98 (95% CI: 0.96-1.00). Conclusions: There were neither positive nor negative clinically meaningful associations between PA and recent MSK disorders among young adult men. The result is surprising and requires further confirmation.

Active Learning Through Video Conferencing to Maintain Physical Activity Among Older Adults: A Pilot Randomized Controlled Trial.

This randomized pilot trial investigated the feasibility of an active learning physical activity intervention through video conferencing and its preliminary effects. Participants comprised community-dwelling older adults who could use e-mail. The intervention group underwent a 12-week active learning intervention via video conferencing to promote a healthy lifestyle, particularly physical activity. The control group received information via e-mail once per week. The amount of physical activity and sedentary behavior was measured using an accelerometer at baseline, postintervention, and 24-week postintervention (36 weeks). Of the 31 participants, 29 were eligible and randomized into two groups (15 for the intervention and 14 for the control). Adherence to the intervention was 83%-100% (mean, 97%). Compared with the control group, the intervention group showed moderate maintenance effects on total physical activity and sedentary behavior at 36 weeks. Active learning physical activity intervention through video conferencing was found to be feasible and contributed to the prevention of physical activity decline in older adults.

Using Wearable Sensors and Machine Learning to Assess Upper Limb Function in Huntington's Disease.

Huntington's disease (HD), like many other neurological disorders, affects both lower and upper limb function that is typically assessed in the clinic - providing a snapshot of disease symptoms. Wearable sensors enable the collection of real-world data that can complement such clinical assessments and provide a more comprehensive insight into disease symptoms. In this context, almost all studies are focused on assessing lower limb function via monitoring of gait, physical activity and ambulation. In this study, we monitor upper limb function during activities of daily living in individuals with HD (n = 16), prodromal HD (pHD, n = 7), and controls (CTR, n = 16) using a wrist-worn wearable sensor, called PAMSys ULM, over seven days. The participants were highly compliant in wearing the sensor with an average daily compliance of 99% (100% for HD, 98% for pHD, and 99% for CTR). Goal-directed movements (GDM) of the hand were detected using a deep learning model, and kinematic features of each GDM were estimated. The collected data was used to predict disease groups (i.e., HD, pHD, and CTR) and clinical scores using a combination of statistical and machine learning-based models. Significant differences in GDM features were observed between the groups. HD participants performed fewer GDMs with long duration (> 7.5 seconds) compared to CTR (p-val = 0.021, d = -0.86). In velocity and acceleration metrics, the highest effect size feature was the entropy of the velocity zero-crossing length segments (HD vs CTR p-val <0.001, d = -1.67; HD vs pHD p-val = 0.043, d=-0.98; CTR vs pHD p-val = 0.046, d=0.96). In addition, this same variable showed a strongest correlation with clinical scores. Classification models achieved good performance in distinguishing HD, pHD and CTR individuals with a balanced accuracy of 67% and a 0.72 recall for the HD group, while regression models accurately predicted clinical scores. Notably the explained variance for the upper extremity function subdomain scale of Unified Huntington's Disease Rating Scale (UHDRS) was the highest, with the model capturing 60% of the variance. Our findings suggest the potential of wearables and machine learning for early identification of phenoconversion, remote monitoring in HD, and evaluating new treatments efficacy in clinical trials and medicine.

Ecological momentary assessment of physical activity and sedentary behaviour in shift workers and non-shift workers: Validation study.

This study examined the criterion validity of an ecological momentary assessment (EMA)-reported physical activity and sedentary time compared with accelerometry in shift workers and non-shift workers. Australian workers (n = 102) received prompts through a mobile EMA app and wore the Actigraph accelerometer on the right hip for 7-10 days. Participants received five EMA prompts per day at 3-hour intervals on their mobile phones. EMA prompts sent to shift workers (SW-T) were tailored according to their work schedule. Non-shift workers (NSW-S) received prompts at standardised times. To assess criterion validity, the association of EMA-reported activities and the Actigraph accelerometer activity counts and number of steps were used. Participants were 36 ± 11 years and 58% were female. On occasions where participants reported physical activity, acceleration counts per minute (CPM) and steps were significantly higher (ß = 1184 CPM, CI 95%: 1034, 1334; ß = 20.9 steps, CI 95%: 18.2, 23.6) than each of the other EMA activities. Acceleration counts and steps were lower when sitting was reported than when no sitting was reported by EMA. Our study showed that EMA-reported physical activity and sedentary time was significantly associated with accelerometer-derived data. Therefore, EMA can be considered to assess shift workers' movement-related behaviours with accelerometers to provide rich contextual data.