Association between upper limb clinical tests and accelerometry metrics for arm use in daily life in children with unilateral cerebral palsy.

PURPOSE: To evaluate the association between upper-limb (UL) clinical tests and UL accelerometry-derived metrics in children with unilateral Cerebral Palsy (CP). METHODS: In this cross-sectional study, twenty children with unilateral CP and Manual Ability Classification System level I-III were included. Outcomes of the Assisting Hand Assessment, Box and Block-Test and accelerometry metrics were collected in the clinical setting and in daily life. UL asymmetry index (i.e., the ratio between the well-functioning UL and the affected UL use) was evaluated in different physical activity levels and relative use of UL was evaluated during daily living. Spearman's correlation was used to determine the association between UL clinical tests and accelerometry metrics in a clinical setting and in daily life. RESULTS: The strongest negative association was between the Assisting Hand Assessment units and accelerometry metrics during the sedentary time in daily life (rs = -0.64). The asymmetries between ULs were highest during the child's sedentary time (asymmetry index: 45.15) compared to when the child was in light (asymmetry index: 23.97) or higher intensity physical activity (asymmetry index: 13.39). The children used both ULs simultaneously for 44% of the time during daily life. CONCLUSION: Accelerometry metrics may provide additional objective information to clinical tests by quantifying the amount of UL movements and the amount of asymmetry between the upper limbs in daily life.

Accelerometer-based metrics of the upper limbs offer additional information about the quantity of upper limb asymmetry and relative use in children and adolescents with unilateral Cerebral Palsy.Accelerometer-based metrics of upper limb asymmetry in sedentary time and different physical activity intensities in daily life can be a complement to clinical tests among children and adolescents with unilateral Cerebral Palsy.

Development of a goal-directed movement intervention (GOAL) using a movement sensor for hospitalized patients: An intervention mapping approach.

OBJECTIVE: To describe the development of a goal-directed movement intervention in two medical wards, including recommendations for implementation and evaluation. DESIGN: Implementation Research. SETTING: Pulmonology and nephrology/gastroenterology wards of the University Medical Centre Utrecht, The Netherlands. PARTICIPANTS: Seven focus groups were executed including 28 nurses, 7 physical therapists and 15 medical specialists. Patients' perceptions were repeatedly assessed during the iterative steps of the intervention development. INTERVENTION: Interventions were targeted to each ward's specific character, following an Intervention Mapping approach using literature and research meetings. Main measures: Intervention components were linked to Behavior Change Techniques and implementation strategies will be selected using the Expert Recommendation Implementing Change tool. Evaluation outcomes like number of patients using the movement intervention will be measured, based on the taxonomy of Proctor. RESULTS: The developed intervention consists of: insight in patients movement behavior (monitoring & feedback), goal setting (goals & planning) and adjustments to the environment (associations & antecedents). The following implementation strategies are recommended: to conduct educational meetings, prepare & identify champions and audit & provide feedback. To measure service and client outcomes, the mean level of physical activity per ward can be evaluated and the Net Promoter Score can be used. CONCLUSION(S): This study shows the development of a goal-directed movement intervention aligned with the needs of healthcare professionals. This resulted in an intervention consisting of feedback & monitoring of movement behavior, goal setting and adjustments in the environment. Using a step-by-step iterative implementation model to guide development and implementation is recommended.

Musculoskeletal Rehabilitation: New Perspectives in Postoperative Care Following Total Knee Arthroplasty Using an External Motion Sensor and a Smartphone Application for Remote Monitoring.

BACKGROUND: The number of total knee replacements performed annually is steadily increasing. Parallel options for postoperative care are decreasing, which reduces patient satisfaction. External devices to support physical rehabilitation and health monitoring will improve patient satisfaction and postoperative care. METHODS: In a prospective, international multicenter study, patients were asked to use an external motion sensor and a smartphone application during the postoperative course of primary total knee arthroplasty. The collected data were transferred to a data platform, allowing for the real-time evaluation of patient data. RESULTS: In three participating centers, 98 patients were included. The general acceptance of using the sensor and app was high, with an overall compliance in study participation rate of up to 76%. The early results showed a significant improvement in the overall quality of life (p < 0.001) and significant reductions in pain (p < 0.01) and depression (p < 0.001). CONCLUSIONS: The early results of this clinical and multicenter study emphasize that there is a high interest in and acceptance of digital solutions in patients' treatment pathways. Motion sensor and smartphone applications support patients in early rehabilitation.

Accuracy of gait and posture classification using movement sensors in individuals with mobility impairment after stroke.

Background: Stroke leads to motor impairment which reduces physical activity, negatively affects social participation, and increases the risk of secondary cardiovascular events. Continuous monitoring of physical activity with motion sensors is promising to allow the prescription of tailored treatments in a timely manner. Accurate classification of gait activities and body posture is necessary to extract actionable information for outcome measures from unstructured motion data. We here develop and validate a solution for various sensor configurations specifically for a stroke population. Methods: Video and movement sensor data (locations: wrists, ankles, and chest) were collected from fourteen stroke survivors with motor impairment who performed real-life activities in their home environment. Video data were labeled for five classes of gait and body postures and three classes of transitions that served as ground truth. We trained support vector machine (SVM), logistic regression (LR), and k-nearest neighbor (kNN) models to identify gait bouts only or gait and posture. Model performance was assessed by the nested leave-one-subject-out protocol and compared across five different sensor placement configurations. Results: Our method achieved very good performance when predicting real-life gait versus non-gait (Gait classification) with an accuracy between 85% and 93% across sensor configurations, using SVM and LR modeling. On the much more challenging task of discriminating between the body postures lying, sitting, and standing as well as walking, and stair ascent/descent (Gait and postures classification), our method achieves accuracies between 80% and 86% with at least one ankle and wrist sensor attached unilaterally. The Gait and postures classification performance between SVM and LR was equivalent but superior to kNN. Conclusion: This work presents a comparison of performance when classifying Gait and body postures in post-stroke individuals with different sensor configurations, which provide options for subsequent outcome evaluation. We achieved accurate classification of gait and postures performed in a real-life setting by individuals with a wide range of motor impairments due to stroke. This validated classifier will hopefully prove a useful resource to researchers and clinicians in the increasingly important field of digital health in the form of remote movement monitoring using motion sensors.

Revisiting the cross-sectional and prospective association of physical activity with body composition and physical fitness in preschoolers: A compositional data approach.

BACKGROUND: Information is limited for the benefits of physical activity (PA) in preschoolers. Previous research using accelerometer-assessed PA may be affected for multicollinearity issues. OBJECTIVES: This study investigated the cross-sectional and prospective associations of sedentary behaviour (SB) and PA with body composition and physical fitness using compositional data analysis. METHODS: Baseline PA and SB were collected in 4-year-old (n = 315) using wrist-worn GT3X+ during seven 24 h-periods. Body composition (air-displacement plethysmography) and physical fitness (PREFIT test battery) were assessed at baseline and at the 12-month follow-up. RESULTS: Increasing vigorous PA at expenses of lower-intensity behaviours for 4-year-old was associated with body composition and physical fitness at cross-sectional and longitudinal levels. For example, reallocating 15 min/day from lower intensities to vigorous PA at baseline was associated with higher fat-free mass index (+0.45 kg/m2 , 95% confidence intervals [CI]: 0.18-0.72 kg/m2 ), higher upper-body strength (+0.6 kg, 95% CI: 0.1-1.19 kg), higher lower-body strength (+8 cm, 95% CI: 3-13 cm), and shorter time in completing the motor fitness test (-0.4 s, 95% CI: -0.82 to [-0.01] s) at the 12-month follow-up. Pairwise reallocations of time indicated that the behaviour replaced was not relevant, as long as vigorous PA was increased. CONCLUSIONS: More time in vigorous PA may imply short- and long-term benefits on body composition and physical fitness in preschoolers. These findings using compositional data analysis corroborate our previously published results using isotemporal substitution models.

Description of movement sensor dataset for dog behavior classification.

Movement sensor data from seven static and dynamic dog behaviors (sitting, standing, lying down, trotting, walking, playing, and (treat) searching i.e. sniffing) was collected from 45 middle to large sized dogs with six degree-of-freedom movement sensors attached to the collar and the harness. With 17 dogs the collection procedure was repeated. The duration of each of the seven behaviors was approximately three minutes. The order of the tasks was varied between the dogs and the two repetitions (for the 17 dogs). The behaviors were annotated post-hoc based on the video recordings made with two camcorders during the tests with one second resolution. The annotations were accurately synchronized with the raw movement sensors data. The annotated data was originally used for training behavior classification machine learning algorithms for classifying the seven behaviors. The developed signal processing and classification algorithms are provided together with the raw measurement data and reference annotations. The description and results of the original investigation that the dataset relates to are found in: P. Kumpulainen, A. Valldeoriola Cardó, S. Somppi, H. Törnqvist, H. Väätäjä, P. Majaranta, Y. Gizatdinova, C. Hoog Antink, V. Surakka, M. V. Kujala, O. Vainio, A. Vehkaoja, Dog behavior classification with movement sensors placed on the harness and the collar, Applied Animal behavior Science, 241 (2021), 105,393.

A Systematic Review of Diagnostic Accuracy and Clinical Applications of Wearable Movement Sensors for Knee Joint Rehabilitation.

In clinical practice, only a few reliable measurement instruments are available for monitoring knee joint rehabilitation. Advances to replace motion capturing with sensor data measurement have been made in the last years. Thus, a systematic review of the literature was performed, focusing on the implementation, diagnostic accuracy, and facilitators and barriers of integrating wearable sensor technology in clinical practices based on a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. For critical appraisal, the COSMIN Risk of Bias tool for reliability and measurement of error was used. PUBMED, Prospero, Cochrane database, and EMBASE were searched for eligible studies. Six studies reporting reliability aspects in using wearable sensor technology at any point after knee surgery in humans were included. All studies reported excellent results with high reliability coefficients, high limits of agreement, or a few detectable errors. They used different or partly inappropriate methods for estimating reliability or missed reporting essential information. Therefore, a moderate risk of bias must be considered. Further quality criterion studies in clinical settings are needed to synthesize the evidence for providing transparent recommendations for the clinical use of wearable movement sensors in knee joint rehabilitation.

Automatic Monitoring of Relevant Behaviors for Crustacean Production in Aquaculture: A Review.

Crustacean farming is a fast-growing sector and has contributed to improving incomes. Many studies have focused on how to improve crustacean production. Information about crustacean behavior is important in this respect. Manual methods of detecting crustacean behavior are usually infectible, time-consuming, and imprecise. Therefore, automatic growth situation monitoring according to changes in behavior has gained more attention, including acoustic technology, machine vision, and sensors. This article reviews the development of these automatic behavior monitoring methods over the past three decades and summarizes their domains of application, as well as their advantages and disadvantages. Furthermore, the challenges of individual sensitivity and aquaculture environment for future research on the behavior of crustaceans are also highlighted. Studies show that feeding behavior, movement rhythms, and reproduction behavior are the three most important behaviors of crustaceans, and the applications of information technology such as advanced machine vision technology have great significance to accelerate the development of new means and techniques for more effective automatic monitoring. However, the accuracy and intelligence still need to be improved to meet intensive aquaculture requirements. Our purpose is to provide researchers and practitioners with a better understanding of the state of the art of automatic monitoring of crustacean behaviors, pursuant of supporting the implementation of smart crustacean farming applications.

Accelerometer Calibration: The Importance of Considering Functionality.

PURPOSE: To compare the accuracy and precision of a hip-worn accelerometer to predict energy cost during structured activities across motor performance and disease conditions. METHODS: 118 adults self-identifying as healthy (n = 44) and those with arthritis (n = 23), multiple sclerosis (n = 18), Parkinson's disease (n = 17), and stroke (n =18) underwent measures of motor performance and were categorized into groups: Group 1, usual; Group 2, moderate impairment; and Group 3, severe impairment. The participants completed structured activities while wearing an accelerometer and a portable metabolic measurement system. Accelerometer-predicted energy cost (metabolic equivalent of tasks [METs]) were compared with measured METs and evaluated across functional impairment and disease conditions. Statistical significance was assessed using linear mixed effect models and Bayesian information criteria to assess model fit. RESULTS: All activities' accelerometer counts per minute (CPM) were 29.5-72.6% less for those with disease compared with those who were healthy. The predicted MET bias was similar across disease, -0.49 (-0.71, -0.27) for arthritis, -0.38 (-0.53, -0.22) for healthy, -0.44 (-0.68, -0.20) for MS, -0.34 (-0.58, -0.09) for Parkinson's, and -0.30 (-0.54, -0.06) for stroke. For functional impairment, there was a graded reduction in CPM for all activities: Group 1, 1,215 CPM (1,129, 1,301); Group 2, 789 CPM (695, 884); and Group 3, 343 CPM (220, 466). The predicted MET bias revealed similar results across the Group 1, -0.37 METs (-0.52, -0.23); Group 2, -0.44 METs (-0.60, -0.28); and Group 3, -0.33 METs (-0.55, -0.13). The Bayesian information criteria showed a better model fit for functional impairment compared with disease condition. CONCLUSION: Using functionality to improve accelerometer calibration could decrease variability and warrants further exploration to improve accelerometer prediction of physical activity.

Assessment of the Shank-to-Vertical Angle While Changing Heel Heights Using a Single Inertial Measurement Unit in Individuals with Incomplete Spinal Cord Injury Wearing an Ankle-Foot-Orthosis.

Previous research showed that an Inertial Measurement Unit (IMU) on the anterior side of the shank can accurately measure the Shank-to-Vertical Angle (SVA), which is a clinically-used parameter to guide tuning of ankle-foot orthoses (AFOs). However, in this context it is specifically important that differences in the SVA are detected during the tuning process, i.e., when adjusting heel height. This study investigated the validity of the SVA as measured by an IMU and its responsiveness to changes in AFO-footwear combination (AFO-FC) heel height in persons with incomplete spinal cord injury (iSCI). Additionally, the effect of heel height on knee flexion-extension angle and internal moment was evaluated. Twelve persons with an iSCI walked with their own AFO-FC in three different conditions: (1) without a heel wedge (refHH), (2) with 5 mm heel wedge (lowHH) and (3) with 10 mm heel wedge (highHH). Walking was recorded by a single IMU on the anterior side of the shank and a 3D gait analysis (3DGA) simultaneously. To estimate validity, a paired t-test and intraclass correlation coefficient (ICC) between the SVAIMU and SVA3DGA were calculated for the refHH. A repeated measures ANOVA was performed to evaluate the differences between the heel heights. A good validity with a mean difference smaller than 1 and an ICC above 0.9 was found for the SVA during midstance phase and at midstance. Significant differences between the heel heights were found for changes in SVAIMU (p = 0.036) and knee moment (p = 0.020) during the midstance phase and in SVAIMU (p = 0.042) and SVA3DGA (p = 0.006) at midstance. Post-hoc analysis revealed a significant difference between the ref and high heel height condition for the SVAIMU (p = 0.005) and knee moment (p = 0.006) during the midstance phase and for the SVAIMU (p = 0.010) and SVA3DGA (p = 0.006) at the instant of midstance. The SVA measured with an IMU is valid and responsive to changing heel heights and equivalent to the gold standard 3DGA. The knee joint angle and knee joint moment showed concomitant changes compared to SVA as a result of changing heel height.

Differences in Weekly Load Distribution Over Two Euroleague Seasons with a Different Head Coach.

The weekly training management and competition loads are important aspects to optimize the performance of professional basketball players. The objectives of the study were (a) to describe the weekly external load (EL), as well as the internal response (IR), of elite basketball players over two consecutive seasons with a different head coach and (b) to compare weekly loads of different competitive densities. The data were collected from 27 elite players from the same team competing in the Spanish first division league (ACB) and EuroLeague during 2017-2018 and 2018-2019 seasons. EL was measured using microsensor technology to determine PlayerLoad values, expressed in arbitrary units (AU). Session rating of perceived exertion (sRPE) was used for IR quantification. Comparisons between the two seasons and of weeks with different competitive densities were made. The inter-week load variability was moderate-high for both seasons. The highest EL values were measured during the weeks with three games (W3) (W3 > W0 > W2 > W1), while the most demanding week for players' IR was observed during weeks with no competition (W0). Additionally, higher EL (d = 0.31) and IR (d = 0.37) values were observed in season 2018-2019 compared to 2017-2018. The results obtained in this study contributed new data on the internal and external load required by professional basketball players in weeks with different number of games and showed that different coaching strategies may demand a different external and internal workload in consecutive seasons. Furthermore, the results highlighted the need to carry out an adequate load management program.

Encouragement-Induced Real-World Upper Limb Use after Stroke by a Tracking and Feedback Device: A Study Protocol for a Multi-Center, Assessor-Blinded, Randomized Controlled Trial.

INTRODUCTION: Retraining the paretic upper limb after stroke should be intense and specific to be effective. Hence, the best training is daily life use, which is often limited by motivation and effort. Tracking and feedback technology have the potential to encourage self-administered, context-specific training of upper limb use in the patients' home environment. The aim of this study is to investigate post-intervention and long-term effects of a wrist-worn activity tracking device providing multimodal feedback on daily arm use in hemiparetic subjects beyond 3 months post-stroke. METHODS AND ANALYSIS: A prospective, multi-center, assessor-blinded, Phase 2 randomized controlled trial with a superiority framework. Sixty-two stroke patients will be randomized in two groups with a 1:1 allocation ratio, stratified based on arm paresis severity (Fugl-Meyer Assessment-Upper Extremity subscale <32 and ≥32). The experimental group receives a wrist-worn activity tracking device providing multimodal feedback on daily arm use for 6 weeks. Controls wear an identical device providing no feedback. Sample size: 31 participants per group, based on a difference of 0.75±1.00 points on the Motor Activity Log-14 Item Version, Amount of Use subscale (MAL-14 AOU), 80% power, two-sided alpha of 0.05, and a 10% attrition rate. Outcomes: primary outcome is the change in patient-reported amount of daily life upper limb use (MAL-14 AOU) from baseline to post-intervention. Secondary outcomes are change in upper limb motor function, upper limb capacity, global disability, patient-reported quality of daily life upper limb use, and quality of life from baseline to post-intervention and 6-week follow-up, as well as compliance, activity counts, and safety. DISCUSSION: The results of this study will show the possible efficacy of a wrist-worn tracking and feedback device on patient-reported amount of daily life upper limb use. ETHICS AND DISSEMINATION: The study is approved by the Cantonal Ethics Committees Zurich, and Northwest and Central Switzerland (BASEC-number 2017-00948) and registered in https://clinicaltrials.gov (NCT03294187) before recruitment started. This study will be carried out in compliance with the Declaration of Helsinki, ICH-GCP, ISO 14155:2011, and Swiss legal and regulatory requirements. Dissemination will include submission to a peer-reviewed journal, patient and healthcare professional magazines, and congress presentations.

State-related differences in the level of psychomotor activity in patients with bipolar disorder - Continuous heart rate and movement monitoring.

Measuring changes in psychomotor activity is a potential tool in the monitoring of the course of affective states in bipolar disorder. Previous studies have been cross-sectional and only some have used objective measures. The aim was to investigate state-related differences in objectively-measured psychomotor activity in bipolar disorder. During a 12 weeks study, repeated measurements of heart rate and movement monitoring over several days were collected during different affective states from 19 outpatients with bipolar disorder. Outcomes included activity energy expenditure (AEE) and trunk acceleration (ACC). Symptoms were clinically assessed using Hamilton Depression Rating Scale (HDRS-17) and Young Mania Rating Scale (YMRS). Compared to patients in a euthymic state, patients in a manic state had significantly higher AEE. Compared to patients in a depressive state, patients in a manic state had significantly higher ACC and AEE. There was a significant diurnal variation in ACC and AEE between affective states. Finally, there was a significant correlation between the severity of manic symptoms and ACC and AEE, respectively. This first study measuring psychomotor activity during different affective states using a combined heart rate and movement sensor supports that psychomotor activity is a core symptom in bipolar disorder that is altered during affective states.

Accelerometer measured sedentary behavior and physical activity in white and black adults: The REGARDS study.

OBJECTIVES: Health disparities between subgroups may be partially due to differences in lifestyle behaviors such as sedentariness and physical activity. To obtain a more accurate description of these two lifestyle behaviors, accelerometry was employed among a large sample of white and black adults (ages 49-99 years) living in the United States. DESIGN: Cross-sectional. METHODS: 7967 participants from the REasons for Geographic and Racial Differences in Stroke cohort wore an Actical™ accelerometer ≥10h/day for ≥4 days. Time (mean minutes/day and proportion of total wear time) spent in sedentary behavior, light intensity physical activity, and moderate-vigorous intensity physical activity was compared by sex, age, body mass index, race, and geographic location. RESULTS: Proportion of total wear time spent in sedentary behavior was 75-90%, light intensity physical activity was 10-23%, and moderate-vigorous intensity physical activity was 0-1.7% across subgroups. Mean moderate-vigorous intensity physical activity was 0-16min/day and associated with 3-12% accumulating ≥150min/wk using a 10-min bout criterion. Persons ≥85 years, those classified obese, persons living in the southeastern United States, and black women were the most inactive. The proportion achieving at least one 10-min bout of moderate-vigorous intensity physical activity per week was only 36%. The number of 10-min bouts/week was 1.5±0.08bouts/week. The distribution of weekly moderate-vigorous intensity physical activity was similar across nearly all subgroups with a distinct reverse J-shaped configuration. CONCLUSIONS: The vast majority of white and black midlife and older adults in this study engaged sparingly in moderate-vigorous intensity physical activity, accumulated tremendous amounts of sedentary behavior, and seldom engaged in continuous bouts of health-enhancing physical activity.

A 6 year longitudinal study of accelerometer-measured physical activity and sedentary time in Swedish adults.

OBJECTIVES: The aim of this study was to investigate changes over six years in physical activity and sedentary behavior assessed with accelerometry in a representative sample of Swedish adults. DESIGN: A longitudinal study over six years. METHODS: The cohort consisted of 1172 participants (46% males) in 2002 and 511 participants (46% males) in 2008, of which 478 (45% males) had valid data on both occasions. Mean (SD) age at baseline was 45 (15) years. To analyze changes over time, a mixed linear model for average intensity physical activity (counts/min) and time in sedentary behavior and light- and moderate- or higher-intensity physical activity was conducted, stratified for sex and age, and adjusted for BMI, education, self-rated health and Δ wear time. RESULTS: Over a six year period no significant changes were seen in the total cohort for average intensity and time in moderate- or higher intensity physical activity. A significant decrease in average intensity physical activity was found for men (p=0.006) and those aged 60+ years at baseline (p<0.001). A significant increase (26 min/day) for sedentary time in the total cohort (p<0.001) and for time in moderate or higher intensity physical activity among women (p<0.001) and those aged 40-59 years at baseline (p=0.014) was found over the follow-up period. CONCLUSIONS: The overall increase in sedentary time and decrease in average physical activity among men and the elderly are of concern, since they might result in an elevated risk of developing chronic diseases.

Electronic monitoring of psychomotor activity as a supplementary objective measure of depression severity.

BACKGROUND: Rating scales used to assess the severity of depression e.g. the Hamilton Depression Rating Scale 17-item (HDRS-17) partly rely on the patient's subjective experience and reporting. Such subjective measures tend to have low reliability and adding objective measures to complement the assessment of depression severity would be a major step forward. AIMS: To investigate correlations between electronic monitoring of psychomotor activity and severity of depression according to HDRS-17. METHODS: A total of 36 patients with unipolar disorder (n = 18) or bipolar disorder (n = 18) and 31 healthy control persons aged 18-60 years were included. Psychomotor activity was measured using a combined heart rate and movement sensor device (Actiheart) for 3 consecutive days, 24 h a day. RESULTS: We found that sleeping heart rate (beats/min) correlated with HDRS-17 in both patients with unipolar disorder and bipolar disorder (unadjusted model: B = 0.46, 95% CI 0.037-0.89, P = 0.034). In contrast, correlations between activity energy expenditure (kJ/kg/day), cardio-respiratory fitness (mlO2/min/kg) and HDRS-17 were non-significant. CONCLUSIONS: These results suggest that measuring sleeping heart rate in non-experimental daily life could be an objective supplementary method to measure the severity of depression and perhaps indicate presence of insomnia.