# Human Pose Detection for Robotic-Assisted and Rehabilitation Environments
## 1 Introduction  
A high demand of services for assisted and rehabilitation environments is expected from the health status of the world due to the COVID-19 pandemic. Currently, according to the WHO (World Health Organization), existing rehabilitation services have been disrupted in 60-70% of countries due to this pandemic in order to avoid human contact. Therefore, countries must face major challenges to ensure the health of their population. Robotic platforms are a great solution to ensure assistance and rehabilitation for disabled people using human-robot interaction (HRI) capabilities. HRI is currently a topic of research that contributes by means of several research approaches for the physical and/or social interaction of humans and robotic systems [1] in order to achieve a goal together. The number of people with congenital and/or acquired disabilities are quickly increasing, and therefore, there are many dependents who lack the necessary autonomy for a fully independent life. Among them, stroke is one of the main causes of these acquired disabilities throughout the world. Acquired brain injury (ABI) is a clinical-functional situation triggered by an injury of any origin that acutely affects the brain, causing neurological deterioration, functional loss, and poor quality of life as a result. It can be due to various causes, with stroke and head trauma the most frequent in our environment. Patients with ABI suffer cognitive and motor sequelae. In stroke patients, motor sequelae are usually more severe in the upper limb. In published studies, it has been reported that 30-60% of hemiplegic patients due to a stroke remain with severely affected upper limbs after 6 months of the event, and only 5-20% manage a complete functional recovery. Physical medicine and rehabilitation are the most important treatment methods in ABI because they help patients reutilize their limbs at maximum capacity. Intensive therapies and repetitive task-based exercises are very effective treatments for motor skills recovery [2]. One of the most important processes of physical therapy requires manual exercises, in which the physiotherapist and the patient must have one-to-one interaction. The goal of the physiotherapist in this process is to help the patients achieve a normal standard of range of motion in their limbs and to strengthen their muscles. Rehabilitation robotic platforms pursue the recovery of impaired motor function. The majority of rehabilitation robotics research to date has focused on passive post-stroke exercises (e.g., [3,4]). The use of assistive robotics in rehabilitation allows the assistance of the physiotherapist in certain exercises that require repeated movements with high precision. The robot can fulfil the requirements of the cyclic movements in rehabilitation. Additionally, robots can successfully control the forces applied and can monitor the therapy results objectively by using their sensors. Robots intended for upper limb rehabilitation can accomplish active and passive bilateral and unilateral motor skills training for the wrist, forearm, and shoulder. MIT-Manus is one of the most well-known upper limb rehabilitation robots [5]. It was developed for unilateral shoulder or elbow rehabilitation. MIME is another well-known upper limb rehabilitation robot, developed for elbow rehabilitation using the master-slave concept [6]. The movement of the master side of the robot is reproduced on the slave side. The 2-DOF robot can perform flexion-extension and pronation-supination movements. The Assistive Rehabilitation and Measurement (ARM) Guide is a bilateral rehabilitation system for upper limb rehabilitation using an industrial robot [7]. It assists the patient in following a trajectory. It also serves as a basis for the evaluation of several key motor impairments, including abnormal tone, incoordination, and weakness. The GENTLE/s system uses a haptic interface and virtual reality techniques for rehabilitation. The patients can move their limbs in a three-dimensional space with the aid of the robot [8].