No abstract

A healthy lifestyle reduces the risk of cardio-vascular disease. As wheelchair-bound individuals with spinal cord injury (SCI) are challenged in their activities, promoting and coaching an active lifestyle is especially relevant. Although there are many commercial activity trackers available for the able-bodied population, including those providing feedback about energy expenditure (EE), activity trackers for the SCI population are largely lacking, or are limited to a small set of activities performed in controlled settings. The aims of the present study were to develop and validate an algorithm based on inertial measurement unit (IMU) data to continuously monitor EE in wheelchair-bound individuals with a SCI, and to establish reference activity values for a healthy lifestyle in this population. For this purpose, EE was measured in 30 subjects each wearing four IMUs during 12 different physical activities, randomly selected from a list of 24 activities of daily living. The proposed algorithm consists of three parts: resting EE estimation based on multi-linear regression, an activity classification using a k-nearest-neighbors algorithm, and EE estimation based on artificial neural networks (ANNs). The mean absolute estimation error for the ANN-based algorithm was 14.4% compared to indirect calorimeter measurements. Based on reference values from the literature and the data collected within this study, we recommend wheeling 3 km per day for a healthy lifestyle in wheelchair-bound SCI individuals. Combining the proposed algorithm with a recommendation for physical activity provides a powerful tool for the promotion of an active lifestyle in the SCI population, thereby reducing the risk for secondary diseases.

Physical activity (PA) has been shown to have a positive influence on functional recovery in patients after a spinal cord injury (SCI). Hence, it can act as a confounder in clinical intervention studies. Wearable sensors are used to quantify PA in various neurological conditions. However, there is a lack of knowledge about the inter-day reliability of PA measures. The objective of this study was to investigate the single-day reliability of various PA measures in patients with a SCI and to propose recommendations on how many days of PA measurements are required to obtain reliable results. For this, PA of 63 wheelchair-dependent patients with a SCI were measured using wearable sensors. Patients of all age ranges (49.3 ± 16.6 years) and levels of injury (from C1 to L2, ASIA A-D) were included for this study and assessed at three to four different time periods during inpatient rehabilitation (2 weeks, 1 month, 3 months, and if applicable 6 months after injury) and after in-patient rehabilitation in their home-environment (at least 6 months after injury). The metrics of interest were total activity counts, PA intensity levels, metrics of wheeling quantity and metrics of movement quality. Activity counts showed consistently high single-day reliabilities, while measures of PA intensity levels considerably varied depending on the rehabilitation progress. Single-day reliabilities of metrics of movement quantity decreased with rehabilitation progress, while metrics of movement quality increased. To achieve a mean reliability of 0.8, we found that three continuous recording days are required for out-patients, and 2 days for in-patients. Furthermore, the results show similar weekday and weekend wheeling activity for in- and out-patients. To our knowledge, this is the first study to investigate the reliability of an extended set of sensor-based measures of PA in both acute and chronic wheelchair-dependent SCI patients. The results provide recommendations for sensor-based assessments of PA in clinical SCI studies.

After spinal cord injury (SCI), levels of independence are commonly assessed with standardized clinical assessments. However, such tests do not provide information about the actual extent of upper limb activities or the impact on independence of bi- versus unilateral usage throughout daily life following cervical SCI. The objective of this study was to correlate activity intensity and laterality of upper extremity activity measured by body-fixed inertial measurement units (IMUs) with clinical assessment scores of independence. Limb-use intensity and laterality of activities performed by the upper extremities was measured in 12 subjects with cervical SCI using four IMUs (positioned on both wrists, on the chest, and on one wheel of the wheelchair). Algorithms capable of reliably detecting self-propulsion and arm activity in a clinical environment were applied to rate functional outcome levels, and were related to clinical independence measures during inpatient rehabilitation. Measures of intensity of upper extremity activity during self-propulsion positively correlated (p < 0.05, r = 0.643) with independence measures related to mobility. Clinical measures of laterality were positively correlated (p < 0.01, r = 0.900) with laterality as measured by IMUs during "daily life," and increased laterality was negatively correlated (p < 0.01, r = -0.739) with independence. IMU sensor technology is sensitive in assessing and quantifying upper limb-use intensity and laterality in human cervical SCI. Continuous and objective movement data of distinct daily activities (i.e., mobility and day-to-day activities) can be related to levels of independence. Therefore, IMU sensor technology is suitable not only for monitoring activity levels during rehabilitation (including during clinical trials) but could also be used to assess levels of participation after discharge.

Wearable sensor assessment tools have proven to be reliable in measuring function in normal and impaired movement disorders during well-defined assessment protocols. While such assessments can provide valid and sensitive measures of upper limb activity in spinal cord injury (SCI), no assessment tool has yet been introduced into unsupervised daily recordings to complement clinical assessments during rehabilitation. The objective of this study was to measure the overall amount of upper-limb activity in subjects with acute SCI using wearable sensors and relate this to lesion characteristics, independence, and function. The overall amount of upper extremity activity counts, measures of wheeling (speed and distance), and limb-use laterality were measured in 30 in-patients with an acute cervical or thoracic SCI three months after injury. The findings were related to the international standards for neurological classification of SCI, the spinal cord independence measure, and the upper extremity motor scores of the Graded and Redefined Assessment of Strength, Sensibility, and Prehension. Overall upper extremity activity counts were successfully recorded in all patients and correlated with the neurological level of injury and independence. Clinical measures of proximal muscle strength were related to overall activity count and peak velocity of wheeling. Compared with paraplegics, tetraplegics showed significantly lower activity counts and increased limb-use laterality. This is the first cross-sectional study showing the feasibility and clinical value of sensor recordings during unsupervised daily activities in rehabilitation. The strong relationship between sensor-based measures and clinical outcomes supports the application of such technology to assess and track changes in function during rehabilitation and in clinical trials.