Alana Elza Fontes da Gama

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.

Rehabilitation motion recognition based on the international biomechanical standards

Abstract Since 1990, the International Society of Biomechanics (ISB) has made efforts to provide uniformity to motion description. However, the majority of user studies and technological systems that use motion recognition for rehabilitation, such as virtual and augmented reality (VR and AR), do not follows this standard. Typically, VR and AR techniques recognize motion by comparing human joint positions to a pre-recorded movement, direction, or position relative to an interactive object. Aiming to fill a lack of biomechanical reference on joint motion recognition and analysis for rehabilitation interactive systems, this paper proposes a movement description and recognition method following the ISB standard. The developed method aims to provide computational solutions which are clinically relevant and that uses clinical jargon known to the rehabilitation therapists. The proposed method will also allow motion analysis independent of users height or its position relative to sensor. We conclude this paper by presenting a comparative analysis of the effectiveness of the Kinect sensors (versions 1 & 2) regarding the recognition of patient exercise motions related to the biomechanical standard. Our solution consists of biomechanical motion classification by identifying in which 3D plane the motion occurs. The motion recognition solution also provides patient posture, motion, and information about incorrect exercise performance. The method was developed by first implementing a body representation and Joint Coordinate System based on ISB standard and then motion angle and biomechanical classifications were performed. Specific methods to measure axial rotations were developed inspired by the traditional goniometry strategy. Also, experiments to evaluate if the method is able to classify the biomechanical motions and, thus, detect whether or not they are being performed correctly were performed using both Kinect v1 and Kinect v2. Motions were performed in correctly and wrongly to also verify false positives. Each classified motion was performed 100 times: 70 correct repetitions (35 at normal speed and 35 fast ones) and 30 wrong ones (out of their respective plane). The motion recognition method showed good efficacy in classifying the biomechanical motions correctly. Most of motions presented great success rate of recognition . higher than 80%, mainly using a 20 degrees tolerance.