Detection of pediatric upper extremity motor activity and deficits with accelerometry

Importance: Affordable, quantitative methods to screen children for developmental delays are needed. Motor milestones can be an indicator of developmental delay and may be used to track developmental progress. Accelerometry offers a way to gather real-world information about pediatric motor behavior. Objective: To develop a referent cohort of pediatric accelerometry from bilateral upper extremities (UEs) and determine whether movement can accurately distinguish those with and without motor deficits. Design, Setting, and Participants: Children aged 0 to 17 years participated in a prospective cohort from December 8, 2014, to December 29, 2017. Children were recruited from Ranken Jordan Pediatric Bridge Hospital, Maryland Heights, Missouri, and Washington University School of Medicine in St Louis, St Louis, Missouri. Typically developing children were included as a referent cohort if they had no history of motor or neurological deficit; consecutive sampling and matching ensured equal representation of sex and age. Children with diagnosed asymmetric motor deficits were included in the motor impaired cohort. Exposures: Bilateral UE motor activity was measured using wrist-worn accelerometers for a total of 100 hours in 25-hour increments. Main Outcomes and Measures: To characterize bilateral UE motor activity in a referent cohort for the purpose of detecting irregularities in the future, total activity and the use ratio between UEs were used to describe typically developing children. Asymmetric impairment was classified using the mono-arm use index (MAUI) and bilateral-arm use index (BAUI) to quantify the acceleration of unilateral movements. Results: A total of 216 children enrolled, and 185 children were included in analysis. Of these, 156 were typically developing, with mean (SD) age 9.1 (5.1) years and 81 boys (52.0%). There were 29 children in the motor impaired cohort, with mean (SD) age 7.4 (4.4) years and 16 boys (55.2%). The combined MAUI and BAUI (mean [SD], 0.86 [0.005] and use ratio (mean [SD], 0.90 [0.008]) had similar F1 values. The area under the curve was also similar between the combined MAUI and BAUI (mean [SD], 0.98 [0.004]) and the use ratio (mean [SD], 0.98 [0.004]). Conclusions and Relevance: Bilateral UE movement as measured with accelerometry may provide a meaningful metric of real-world motor behavior across childhood. Screening in early childhood remains a challenge; MAUI may provide an effective method for clinicians to measure and visualize real-world motor behavior in children at risk for asymmetrical deficits

Validation of actigraphy for sleep measurement in children with cerebral palsy

OBJECTIVES: Sleep issues are common in children with cerebral palsy (CP), although there are challenges in obtaining objective data about their sleep patterns. Actigraphs measure movement to quantify sleep but their accuracy in children with CP is unknown. Our goals were to validate actigraphy for sleep assessment in children with CP and to study their sleep patterns in a cross-sectional cohort study. METHODS: We recruited children with (N = 13) and without (N = 13) CP aged 2-17 years (mean age 9 y 11mo [SD 4 y 10mo] range 4-17 y; 17 males, 9 females; 54% spastic quadriplegic, 23% spastic diplegic, 15% spastic hemiplegic, 8% unclassified CP). We obtained wrist and forehead actigraphy with concurrent polysomnography for one night, and home wrist actigraphy for one week. We developed actigraphy algorithms and evaluated their accuracy (agreement with polysomnography-determined sleep versus wake staging), sensitivity (sleep detection), and specificity (wake detection). RESULTS: Our actigraphy algorithms had median 72-80% accuracy, 87-91% sensitivity, and 60-71% specificity in children with CP and 86-89% accuracy, 88-92% sensitivity, and 70-75% specificity in children without CP, with similar accuracies in wrist and forehead locations. Our algorithms had increased specificity and accuracy compared to existing algorithms, facilitating detection of sleep disruption. Children with CP showed lower sleep efficiency and duration than children without CP. CONCLUSIONS: Actigraphy is a valid tool for sleep assessment in children with CP. Children with CP have worse sleep efficiency and duration

Toward a more comprehensive assessment of school age children with hemiplegic cerebral palsy

BACKGROUND: Cerebral palsy (CP) is the leading cause of disability in children. While motor deficits define CP, many patients experience behavioral and cognitive deficits which limit participation. The purpose of this study was to contribute to our understanding of developmental delay and how to measure these deficits among children with CP. METHODS: Children 5 to 15 years with hemiplegic CP were recruited. Cognition and motor ability were assessed. The brain injury associated with observed motor deficits was identified. Accelerometers measured real-world bilateral upper extremity movement and caregivers completed behavioral assessments. RESULTS: Eleven children participated, 6 with presumed perinatal stroke. Four children scored below average intelligence quotient while other measures of cognition were within normal limits (except processing speed). Motor scores confirmed asymmetrical deficits. Approximately one third of scores indicated deficits in attention, behavior, or depression. CONCLUSIONS: Our findings corroborate that children with CP experience challenges that are broader than motor impairment alone. Despite the variation in brain injury, all participants completed study procedures. IMPLICATIONS: Our findings suggest that measuring behavior in children with CP may require a more comprehensive approach and that caregivers are amenable to using online collection tools which may assist in addressing the therapeutic needs of children with CP

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Non peer reviewe

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

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Table1_Referent data for investigations of upper limb accelerometry: harmonized data from three cohorts of typically-developing children.docx

AimThe rise of wearable sensing technology shows promise for addressing the challenges of measuring motor behavior in pediatric populations. The current pediatric wearable sensing literature is highly variable with respect to the number of sensors used, sensor placement, wearing time, and how data extracted from the sensors are analyzed. Many studies derive conceptually similar variables via different calculation methods, making it hard to compare across studies and clinical populations. In hopes of moving the field forward, this report provides referent upper limb wearable sensor data from accelerometers on 25 variables in typically-developing children, ages 3–17 years.MethodsThis is a secondary analysis of data from three pediatric cohorts of children 3–17 years of age. Participants (n = 222) in the cohorts wore bilateral wrist accelerometers for 2–4 days for a total of 622 recording days. Accelerometer data were reprocessed to compute 25 variables that quantified upper limb movement duration, intensity, symmetry, and complexity. Analyses examined the influence of hand dominance, age, gender, reliability, day-to-day stability, and the relationships between variables.ResultsThe majority of variables were similar on the dominant and non-dominant sides, declined slightly with age, and were not different between boys and girls. ICC values were moderate to excellent. Variation within individuals across days generally ranged from 3% to 32%. A web-based R shiny object is available for data viewing.InterpretationWith the use of wearable movement sensors increasing rapidly, these data provide key, referent information for researchers as they design studies, and analyze and interpret data from neurodevelopmental and other pediatric clinical populations. These data may be of particularly high value for pediatric rare diseases.</p

Image1_Referent data for investigations of upper limb accelerometry: harmonized data from three cohorts of typically-developing children.jpeg

AimThe rise of wearable sensing technology shows promise for addressing the challenges of measuring motor behavior in pediatric populations. The current pediatric wearable sensing literature is highly variable with respect to the number of sensors used, sensor placement, wearing time, and how data extracted from the sensors are analyzed. Many studies derive conceptually similar variables via different calculation methods, making it hard to compare across studies and clinical populations. In hopes of moving the field forward, this report provides referent upper limb wearable sensor data from accelerometers on 25 variables in typically-developing children, ages 3–17 years.MethodsThis is a secondary analysis of data from three pediatric cohorts of children 3–17 years of age. Participants (n = 222) in the cohorts wore bilateral wrist accelerometers for 2–4 days for a total of 622 recording days. Accelerometer data were reprocessed to compute 25 variables that quantified upper limb movement duration, intensity, symmetry, and complexity. Analyses examined the influence of hand dominance, age, gender, reliability, day-to-day stability, and the relationships between variables.ResultsThe majority of variables were similar on the dominant and non-dominant sides, declined slightly with age, and were not different between boys and girls. ICC values were moderate to excellent. Variation within individuals across days generally ranged from 3% to 32%. A web-based R shiny object is available for data viewing.InterpretationWith the use of wearable movement sensors increasing rapidly, these data provide key, referent information for researchers as they design studies, and analyze and interpret data from neurodevelopmental and other pediatric clinical populations. These data may be of particularly high value for pediatric rare diseases.</p