Goal-Directed Personalized Upper Limb Intensive Therapy (PULIT) for Children With Hemiparesis: A Retrospective Analysis

Importance: Children with hemiparesis experience limitations in activities of daily living (ADLs) as a result of upper limb impairments. To address these limitations, we developed a group-based Personalized Upper Limb Intensive Therapy (PULIT) program combining modified constraint-induced movement therapy, bimanual intensive therapy, and exergame-based robotics. Objective: To determine the effectiveness of PULIT in helping children with upper limb impairments achieve individually set goals and enable transfer of the attained motor skills into ADLs. Design: Retrospective analysis. Setting: Day camp at a pediatric rehabilitation clinic in Switzerland. Participants: Twenty-three children with upper limb impairment (unilateral cerebral palsy, n = 16; acquired brain injury, n = 7); 13 boys and 10 girls (M age = 7 yr, 8 mo, SD = 2 yr, 1 mo; Manual Ability Classification System Level I-IV). Intervention: Thirty hours of PULIT over the course of 8 days. Outcomes and measures: Goal attainment scaling (GAS) was assessed on the first and last day of intervention. The Canadian Occupational Performance Measure (COPM) and dexterity tests, such as the Box and Block Test (BBT), were administered 3 wk before and 3 wk after the intervention. Results: Total goal achievement was 85.7%. GAS, parent- and child-rated COPM Performance and Satisfaction, and the BBT of the affected and dominant upper limb improved significantly. Conclusions and relevance: PULIT effectively increases children's dexterity of the impaired and dominant upper limb, improves ADL performance, and achieves individual goals. This retrospective analysis could serve as a basis for a future randomized trial. What This Article Adds: This article informs occupational therapy practitioners about a therapy program that includes conventional and rehabilitation technology interventions and enables children with hemiparesis of the upper limb to improve relevant ADL tasks in 8 days' time

Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent

Objective: Measurements of heart rate variability (HRV) during sleep have become increasingly popular as sleep could provide an optimal state for HRV assessments. While sleep stages have been reported to affect HRV, the effect of sleep stages on the variance of HRV parameters were hardly investigated. We aimed to assess the variance of HRV parameters during the different sleep stages. Further, we tested the accuracy of an algorithm using HRV to identify a 5-min segment within an episode of slow wave sleep (SWS, deep sleep). Methods: Polysomnographic (PSG) sleep recordings of 3 nights of 15 healthy young males were analyzed. Sleep was scored according to conventional criteria. HRV parameters of consecutive 5-min segments were analyzed within the different sleep stages. The total variance of HRV parameters was partitioned into between-subjects variance, between-nights variance, and between-segments variance and compared between the different sleep stages. Intra-class correlation coefficients of all HRV parameters were calculated for all sleep stages. To identify an SWS segment based on HRV, Pearson correlation coefficients of consecutive R-R intervals (rRR) of moving 5-min windows (20-s steps). The linear trend was removed from the rRR time series and the first segment with rRR values 0.1 units below the mean rRR for at least 10 min was identified. A 5-min segment was placed in the middle of such an identified segment and the corresponding sleep stage was used to assess the accuracy of the algorithm. Results: Good reproducibility within and across nights was found for heart rate in all sleep stages and for high frequency (HF) power in SWS. Reproducibility of low frequency (LF) power and of LF/HF was poor in all sleep stages. Of all the 5-min segments selected based on HRV data, 87% were accurately located within SWS. Conclusions: SWS, a stable state that, in contrast to waking, is unaffected by internal and external factors, is a reproducible state that allows reliable determination of heart rate, and HF power, and can satisfactorily be detected based on R-R intervals, without the need of full PSG. Sleep may not be an optimal condition to assess LF power and LF/HF power ratio

Heart rate variability during deep sleep offers a time-efficient alternative to morning supine measurements - a study in world class alpine skiers

BACKGROUND/AIM There is increasing popularity for athletes to use heart rate variability (HRV) to tailor training. A time-efficient method is HRV assessment during deep sleep. The aim was to validate the selection of deep sleep segments identified by RR-intervals with simultaneous electroencephalography (EEG) recordings and to compare HRV parameters of these segments with those of standard morning supine measurements. METHODS In 11 world class alpine- skiers, RR-intervals were monitored during ten nights and simultaneous EEGs were recorded in 2-4 nights. Deep sleep was determined from the HRV signal and verified by delta power from the EEG recordings. Four further segments were chosen for HRV determination, namely a 4-h segment from midnight to 4 am, and three 5 min segments: one just before awakening, one after awakening in supine position and one in standing after orthostatic challenge. Training load was recorded every day. RESULTS A total of 80 night and 68 morning measurements of 9 athletes were analyzed. Good correspondence between the phases selected by RR-intervals versus those selected by EEG was found. Concerning root-mean-squared-difference of successive RR-intervals (RMSSD), a marker for parasympathetic activity, the best relationship with the morning supine measurement was found in deep sleep. CONCLUSIONS HRV is a simple tool for approximating deep sleep phases and HRV measurement during deep sleep could provide a time-efficient alternative to HRV in supine position

Relation of heart rate and its variability during sleep with age, physical activity, and body composition in young children

Background: Recent studies have claimed a positive effect of physical activity and body composition on vagal tone. In pediatric populations, there is a pronounced decrease in heart rate with age. While this decrease is often interpreted as an age-related increase in vagal tone, there is some evidence that it may be related to a decrease in intrinsic heart rate. This factor has not been taken into account in most previous studies. The aim of the present study was to assess the association between physical activity and/or body composition and heart rate variability (HRV) independently of the decline in heart rate in young children. Methods: Anthropometric measurements were taken in 309 children aged 2-6 years. Ambulatory electrocardiograms were collected over 14-18 h comprising a full night and accelerometry over 7 days. HRV was determined of three different night segments: (1) over 5 min during deep sleep identified automatically based on HRV characteristics; (2) during a 20 min segment starting 15 min after sleep onset; (3) over a 4-h segment between midnight and 4 a.m. Linear models were computed for HRV parameters with anthropometric and physical activity variables adjusted for heart rate and other confounding variables (e.g., age for physical activity models). Results: We found a decline in heart rate with increasing physical activity and decreasing skinfold thickness. HRV parameters decreased with increasing age, height, and weight in HR-adjusted regression models. These relationships were only found in segments of deep sleep detected automatically based on HRV or manually 15 min after sleep onset, but not in the 4-h segment with random sleep phases. Conclusions: Contrary to most previous studies, we found no increase of standard HRV parameters with age, however, when adjusted for heart rate, there was a significant decrease of HRV parameters with increasing age. Without knowing intrinsic heart rate correct interpretation of HRV in growing children is impossible