Validation of Angle Estimation Based on Body Tracking Data from RGB-D and RGB Cameras for Biomechanical Assessment.

Motion analysis is an area with several applications for health, sports, and entertainment. The high cost of state-of-the-art equipment in the health field makes it unfeasible to apply this technique in the clinics' routines. In this vein, RGB-D and RGB equipment, which have joint tracking tools, are tested with portable and low-cost solutions to enable computational motion analysis. The recent release of Google MediaPipe, a joint inference tracking technique that uses conventional RGB cameras, can be considered a milestone due to its ability to estimate depth coordinates in planar images. In light of this, this work aims to evaluate the measurement of angular variation from RGB-D and RGB sensor data against the Qualisys Tracking Manager gold standard. A total of 60 recordings were performed for each upper and lower limb movement in two different position configurations concerning the sensors. Google's MediaPipe usage obtained close results compared to Kinect V2 sensor in the inherent aspects of absolute error, RMS, and correlation to the gold standard, presenting lower dispersion values and error metrics, which is more positive. In the comparison with equipment commonly used in physical evaluations, MediaPipe had an error within the error range of short- and long-arm goniometers.

MirrARbilitation: A clinically-related gesture recognition interactive tool for an AR rehabilitation system.

BACKGROUND AND OBJECTIVE: Interactive systems for rehabilitation have been widely investigated for motivational purposes. However, more attention should be given to the manner in which user movements are recognized and categorized. This paper aims to evaluate the efficacy of using a clinically-related gesture recognition tool, based on the international biomechanical standards (ISB) for the reporting of human joint motion, for the development of an interactive augmented reality (AR) rehabilitation system -mirrARbilitation. METHODS: This work presents an AR rehabilitation system based on ISB standards, which enables the system to interact and to be configured according to therapeutic needs. The Kinect(TM) skeleton tracking technology was exploited and a new movement recognition method was developed to recognize and classify biomechanical movements. Further, our mirrARbilitation system provides exercise instructions while simultaneously motivating the patient. The system was evaluated on a cohort of 33 patients, physiotherapists, and software developers when performing shoulder abduction therapy exercises. Tests were performed in three moments: (i) users performed the exercise until they feel tired without the help of the system, (ii) the same however using the mirrARbilitation for motivation and guidance, and (iii) users performed the exercise again without the system. Users performing the movement without the help of the system worked as baseline reference. RESULTS: We demonstrated that the percentage of correct exercises, measured by the movement analysis method we developed, improved from 69.02% to 93.73% when users interacted with the mirrARbilitation. The number of exercise repetitions also improved from 34.06 to 66.09 signifying that our system increased motivation of the users. The system also prevented the users from performing the exercises in a completely wrong manner. Finally, with the help of our system the users' worst result was performing 73.68% of the rehabilitation movements correctly. Besides the engagement, these results suggest that the use of biomechanical standards to recognize movements is valuable in guiding users during rehabilitation exercises. CONCLUSION: The proposed system proved to be efficient by improving the user engagement and exercise performance outcomes. The results also suggest that the use of biomechanical standards to recognize movements is valuable in guiding users during rehabilitation exercises.

Acute effects of incremental inspiratory loads on compartmental chest wall volume and predominant activity frequency of inspiratory muscle.

AIM: This research aims to analyze the acute effect of incremental inspiratory loads on respiratory pattern and on the predominant activity frequency of inspiratory muscle, taking into account differences in gender responses. Optoelectronic Plethysmography was performed during loads in 39 healthy subjects (20 women), placing 89 markers on the thoracic-abdominal wall to obtain total and regional volumes. Surface electromyography (SEMG) was taken simultaneously on the Sternocleidomastoid and Diaphragm muscles, to calculate the predominant muscle activity frequency through wavelet analysis. Inspiratory loads were performed using Threshold(®)with 2 min of breathing at different levels, ranging from a load of 10 cmH(2)O plus 5 cmH(2)O to 40 cmH(2)O or fatigue. RESULTS: Inspiratory Time increased during loads. Total and compartmental volumes increased with different regions, changing at different loads. These changes in volume occur earlier in women (20 cmH(2)O) than in men (30 cmH(2)O). The predominant activity frequency of Sternocleidmastoid muscle decreased at 30 cmH(2)O, while Diaphragm activity decreased at 40 cmH(2)O. CONCLUSION: The acute effects of incremental inspiratory loads are increases of total and regional volumes and inspiratory time. As for muscle activity, the predominant activity frequency declined in Sternocleidomastoid and Diaphragm muscles, but at different loads. Such respiratory and SEMG patterns and gender differences should be considered when clinical interventions are performed.