Dipartimento Ingegneria Industriale, Università di Padova, Via Venezia 1, 35131 Padova, Italy.
Dipartimento Ingegneria Industriale, Università di Firenze, Via Santa Marta 3, 50100 Firenze, Italy.
Sensors (Basel). 2021 Dec 28;22(1):184. doi: 10.3390/s22010184.
Home-based rehabilitation is becoming a gold standard for patient who have undergone knee arthroplasty or full knee replacement, as it helps healthcare costs to be minimized. Nevertheless, there is a chance of increasing adverse health effects in case of home care, primarily due to the patients' lack of motivation and the doctors' difficulty in carrying out rigorous supervision. The development of devices to assess the efficient recovery of the operated joint is highly valued both for the patient, who feels encouraged to perform the proper number of activities, and for the doctor, who can track him/her remotely. Accordingly, this paper introduces an interactive approach to angular range calculation of hip and knee joints based on the use of low-cost devices which can be operated at home. First, the patient's body posture is estimated using a 2D acquisition method. Subsequently, the 3D posture is evaluated by using the depth information coming from an RGB-D sensor. Preliminary results show that the proposed method effectively overcomes many limitations by fusing the results obtained by the state-of-the-art robust 2D pose estimation algorithms with the 3D data of depth cameras by allowing the patient to be correctly tracked during rehabilitation exercises.
居家康复正在成为膝关节置换或全膝关节置换患者的黄金标准,因为它有助于将医疗成本降至最低。然而,在居家护理的情况下,患者缺乏动力和医生难以进行严格监督,有可能会增加不良健康影响的风险。开发用于评估手术关节恢复效率的设备对于患者和医生都非常重要,因为患者可以感到鼓励,进行适当数量的活动,而医生可以远程跟踪他/她。因此,本文提出了一种基于使用低成本设备的髋关节和膝关节角度范围计算的交互方法,这些设备可以在家中操作。首先,使用二维采集方法估计患者的身体姿势。随后,通过使用来自 RGB-D 传感器的深度信息来评估三维姿势。初步结果表明,该方法通过融合最先进的鲁棒二维姿态估计算法的结果和深度相机的三维数据,有效地克服了许多限制,允许患者在康复运动期间被正确跟踪。