Inertial measurement unit (IMU) records of human movement can be converted into joint angles using a sensor-to-segment calibration, also called functional calibration. This study aims to compare the accuracy and reproducibility of four functional calibration procedures for the 3D tracking of the lower limb joint angles of young healthy individuals in gait. Three methods based on segment rotations and one on segment accelerations were used to compare IMU records with an optical system for their accuracy and reproducibility. The squat functional calibration movement, offering a low range of motion of the shank, provided the least accurate measurements. A comparable accuracy was obtained in other methods with a root mean square error below 3.6° and an absolute difference in amplitude below 3.4°. The reproducibility was excellent in the sagittal plane (intra-class correlation coefficient (ICC) > 0.91, standard error of measurement (SEM) < 1.1°), good to excellent in the transverse plane (ICC > 0.87, SEM < 1.1°), and good in the frontal plane (ICC > 0.63, SEM < 1.2°). The better accuracy for proximal joints in calibration movements using segment rotations was traded to distal joints in calibration movements using segment accelerations. These results encourage further applications of IMU systems in unconstrained rehabilitative contexts.

Introduction: To assess activity limitations in people with haemophilia (PwH), the self‐reported Haemophilia Activity List (HAL) is widely employed, despite several methodological limitations impacting the interpretation of categorical scores. Modern psychometric approaches avoid these limitations by using a probabilistic model, such as the Rasch model. The ACTIVLIM is a Rasch‐built measurement of activity limitations previously validated in several clinical conditions like neuromuscular disorders.Aims: This study sought to develop the ACTIVLIM‐Hemo, meaning an ACTIVLIM scale version specifically adapted to assess daily activity limitations in adult PwH.Methods: Daily activities were assessed as “impossible,” “difficult” or “easy” by 114 PwH (median age of 44 years) with 63 of them reassessed after 12 days. The Rasch Rating Scale model was used to identify activities delineating a unidimensional and linear scale unbiased by demographic and clinical status. Concurrent validity was determined through correlation with the HAL sub‐scores and sum score.Results: The ACTIVLIM‐Hemo included 22 pertinent activities, with difficulties independent of demographic and clinical conditions, allowing a reliable measure of activity limitations (PSI = .92) expressed on a linear and unidimensional scale in PwH (7%–100 % range, ceiling effect of 1/114) with excellent test‐retest reliability (ICC = .978). Spearman rank correlations between ACTIVLIM‐Hemo and HAL sub‐scores ranged between .623 and .869.Conclusions: The ACTIVLIM‐Hemo is an easy‐to‐administer, valid and reliable alternative to HAL in assessing activity limitations in PwH. Its invariant scale can be used across conditions and time to compare the functional status of PwH over a wide measurement range.

The ability to monitor activities of daily living in the natural environments of patients could become a valuable tool for various clinical applications. In this paper, we show that a simple algorithm is capable of classifying manual activities of daily living (ADL) into categories using data from wrist- and finger-worn sensors. Six participants without pathology of the upper limb performed 14 ADL. Gyroscope signals were used to analyze the angular velocity pattern for each activity. The elaboration of the algorithm was based on the examination of the activity at the different levels (hand, fingers and wrist) and the relationship between them for the duration of the activity. A leave-one-out cross-validation was used to validate our algorithm. The algorithm allowed the classification of manual activities into five different categories through three consecutive steps, based on hands ratio (i.e., activity of one or both hands) and fingers-to-wrist ratio (i.e., finger movement independently of the wrist). On average, the algorithm made the correct classification in 87.4% of cases. The proposed algorithm has a high overall accuracy, yet its computational complexity is very low as it involves only averages and ratios.

(1) Background: Hand and Arm Bimanual Intensive Therapy Including Lower Extremities (HABIT-ILE) is a high-dose evidence-based neurorehabilitation. This study aims to develop and validate a protocol using three inertial measurement units (IMUs) to objectively document upper and lower extremities’ (UE; LE) motor activity during a HABIT-ILE intervention in chronic stroke adults. (2) Method: Thirteen adults (57.1 y ± 11.3) who completed 65 h of HABIT-ILE (2 weeks, 6.5 h/d) were included. Daily motor activity was recorded with IMUs placed on both wrists and one thigh with nine IMU-derived variables extracted to evaluate motor activity and posture. Each variable was correlated with baseline abilities and day-to-day patterns were observed with subgroup analyses based on baseline dexterity and walking endurance. Day-to-day patterns were highlighted based on mean values and effect size analyses. (3) Results: Only the Magnitude and Use ratios showed high correlations with baseline abilities, with a day-to-day specific pattern highlighted for participants with moderate to good dexterity at baseline. (4) Conclusions: All participants reported a high level of engagement during HABIT-ILE independently of their baseline abilities. Although we could not detect a global trend to document the content of a HABIT-ILE intervention, these exploratory results suggest IMU monitoring to be relevant to characterize therapeutic content.