Multidimensional Measures of Physical Activity and Their Association with Gross Motor Capacity in Children and Adolescents with Cerebral Palsy

Abstract

The current lack of adapted performance metrics leads clinicians to focus on what children with cerebral palsy (CP) do in a clinical setting, despite the ongoing debate on whether capacity (what they do at best) adequately reflects performance (what they do in daily life). Our aim was to measure these children’s habitual physical activity (PA) and gross motor capacity and investigate their relationship. Using five synchronized inertial measurement units (IMU) and algorithms adapted to this population, we computed 22 PA states integrating the type (e.g., sitting, walking, etc.), duration, and intensity of PA. Their temporal sequence was visualized with a PA barcode from which information about pattern complexity and the time spent in each of the six simplified PA states (PAS; considering PA type and duration, but not intensity) was extracted and compared to capacity. Results of 25 children with CP showed no strong association between motor capacity and performance, but a certain level of motor capacity seems to be a prerequisite for the achievement of higher PAS. Our multidimensional performance measurement provides a new method of PA assessment in this population, with an easy-to-understand visual output (barcode) and objective data for clinical and scientific use.

A Study on Physical Exercise and General Mobility in People with Cerebral Palsy: Health through Costless Routines

“…However, the mobility level is not always linked to how active a person is. Some people with low mobility show higher levels of PA than other people with better motor functions and with a SB [77]. Most people at ASPACE did light-intensity exercise and required a complete therapist support (45%) or frequent help (25%), which is explained by the severity of their mobility impairments.…”

“…The information delivered by these devices is directly linked to intensity of the PA. Accelerometers can therefore be used to estimate energy expenditure during PA [76]. The placement of these devices depends on the type of activity to be measured and the subject's abilities [50,77,78]. When individuals have problems standing up, the accelerometer is normally placed on the chest or on the wrist of the dominant hand [42,77].…”

“…The placement of these devices depends on the type of activity to be measured and the subject's abilities [50,77,78]. When individuals have problems standing up, the accelerometer is normally placed on the chest or on the wrist of the dominant hand [42,77]. As mentioned briefly above, these devices can be used to distinguish between sedentary periods, intensity levels in PA and different kinds of activities.…”

Sensor-based outcomes to monitor everyday life motor activities of children and adolescents with neuromotor impairments: A survey with health professionals

“…So far, several sensor systems and algorithms have been developed for a pediatric population. These algorithms cover five of the twelve most relevant outcomes, namely the duration of body positions ( 8 , 9 ), the amount of active wheeling ( 10 , 11 ), the hand use laterality and the distinction between unimanual and bimanual activities ( 13 ), and the duration, distance, and speed of walking activities ( 7 – 10 , 12 ). However, none of these algorithms provide a comprehensive overview of these outcomes and based on the authors' knowledge, the remaining outcomes of the top twelve (i.e., the number of transfers, the risk of falling, the use of walking aids, the number of climbed stairs, and the amount of cycling, dressing, eating and drinking activities) have not been addressed, yet.…”

“…Besides this large variety of algorithms designed for adults, there is also a handful of algorithms available which were specifically developed for a pediatric population (7)(8)(9)(10)(11)(12)(13). These algorithms estimate the time spent in sedentary, standing, walking, running, cycling, or upper limb activities; discriminate between active and passive wheelchair mobility; calculate an index of hand use laterality; and determine gait parameters, such as stride time and length.…”