Research Group of Pattern Recognition, University of Siegen, Germany; College of Information Technology, University of the Punjab, Pakistan.
Research Group of Pattern Recognition, University of Siegen, Germany.
Int J Med Inform. 2018 May;113:85-95. doi: 10.1016/j.ijmedinf.2018.02.010. Epub 2018 Feb 25.
A neurological illness is t he disorder in human nervous system that can result in various diseases including the motor disabilities. Neurological disorders may affect the motor neurons, which are associated with skeletal muscles and control the body movement. Consequently, they introduce some diseases in the human e.g. cerebral palsy, spinal scoliosis, peripheral paralysis of arms/legs, hip joint dysplasia and various myopathies. Vojta therapy is considered a useful technique to treat the motor disabilities. In Vojta therapy, a specific stimulation is given to the patient's body to perform certain reflexive pattern movements which the patient is unable to perform in a normal manner. The repetition of stimulation ultimately brings forth the previously blocked connections between the spinal cord and the brain. After few therapy sessions, the patient can perform these movements without external stimulation. In this paper, we propose a computer vision-based system to monitor the correct movements of the patient during the therapy treatment using the RGBD data. The proposed framework works in three steps. In the first step, patient's body is automatically detected and segmented and two novel techniques are proposed for this purpose. In the second step, a multi-dimensional feature vector is computed to define various movements of patient's body during the therapy. In the final step, a multi-class support vector machine is used to classify these movements. The experimental evaluation carried out on the large captured dataset shows that the proposed system is highly useful in monitoring the patient's body movements during Vojta therapy.
一种神经系统疾病是指人类神经系统的紊乱，可导致各种疾病，包括运动障碍。神经紊乱可能会影响运动神经元，这些神经元与骨骼肌有关，控制着身体的运动。因此，它们会在人体内引发一些疾病，如脑瘫、脊柱侧凸、手臂/腿部周围瘫痪、髋关节发育不良和各种肌病。Vojta 疗法被认为是治疗运动障碍的一种有效技术。在 Vojta 疗法中，会对患者的身体进行特定的刺激，以执行某些反射性的模式运动，而这些运动患者无法以正常方式进行。重复刺激最终会在脊髓和大脑之间产生以前被阻断的连接。经过几次治疗后，患者可以在没有外部刺激的情况下进行这些运动。在本文中，我们提出了一种基于计算机视觉的系统，使用 RGBD 数据来监测治疗过程中患者的正确运动。该框架分三个步骤工作。在第一步中，自动检测和分割患者的身体，并为此提出了两种新的技术。在第二步中，计算多维特征向量来定义治疗过程中患者身体的各种运动。在最后一步中，使用多类支持向量机对这些运动进行分类。在大型捕获数据集上进行的实验评估表明，该系统在监测 Vojta 疗法期间患者的身体运动方面非常有用。
