Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore.
Centre for Rehabilitation Excellence (CORE), Tan Tock Seng Hospital, Singapore, Singapore.
J Neuroeng Rehabil. 2023 Mar 1;20(1):29. doi: 10.1186/s12984-023-01149-0.
Aging degrades the balance and locomotion ability due to frailty and pathological conditions. This demands balance rehabilitation and assistive technologies that help the affected population to regain mobility, independence, and improve their quality of life. While many overground gait rehabilitation and assistive robots exist in the market, none are designed to be used at home or in community settings.
A device named Mobile Robotic Balance Assistant (MRBA) is developed to address this problem. MRBA is a hybrid of a gait assistive robot and a powered wheelchair. When the user is walking around performing activities of daily living, the robot follows the person and provides support at the pelvic area in case of loss of balance. It can also be transformed into a wheelchair if the user wants to sit down or commute. To achieve instability detection, sensory data from the robot are compared with a predefined threshold; a fall is identified if the value exceeds the threshold. The experiments involve both healthy young subjects and an individual with spinal cord injury (SCI). Spatial Parametric Mapping is used to assess the effect of the robot on lower limb joint kinematics during walking. The instability detection algorithm is evaluated by calculating the sensitivity and specificity in identifying normal walking and simulated falls.
When walking with MRBA, the healthy subjects have a lower speed, smaller step length and longer step time. The SCI subject experiences similar changes as well as a decrease in step width that indicates better stability. Both groups of subjects have reduced joint range of motion. By comparing the force sensor measurement with a calibrated threshold, the instability detection algorithm can identify more than 93% of self-induced falls with a false alarm rate of 0%.
While there is still room for improvement in the robot compliance and the instability identification, the study demonstrates the first step in bringing gait assistive technologies into homes. We hope that the robot can encourage the balance-impaired population to engage in more activities of daily living to improve their quality of life. Future research includes recruiting more subjects with balance difficulty to further refine the device functionalities.
由于虚弱和病理状况，衰老会降低平衡和移动能力。这需要平衡康复和辅助技术，帮助受影响的人群重新获得活动能力、独立性，并提高他们的生活质量。虽然市场上有许多地面步态康复和辅助机器人，但没有一个是专门为家庭或社区环境设计的。
开发了一种名为 Mobile Robotic Balance Assistant (MRBA) 的设备来解决这个问题。MRBA 是一种步态辅助机器人和动力轮椅的混合体。当用户在周围进行日常生活活动时，机器人会跟随人，并在平衡丧失时提供骨盆区域的支撑。如果用户想坐下或通勤，它也可以转换成轮椅。为了实现不稳定性检测，将机器人的传感器数据与预定义的阈值进行比较；如果值超过阈值，则识别为跌倒。实验涉及健康的年轻受试者和一名脊髓损伤（SCI）患者。使用空间参数映射来评估机器人对行走时下肢关节运动学的影响。通过计算识别正常行走和模拟跌倒的灵敏度和特异性来评估不稳定性检测算法。
当使用 MRBA 行走时，健康受试者的速度较慢，步长较小，步时较长。SCI 受试者也经历了类似的变化，以及步宽减小，这表明稳定性更好。两组受试者的关节活动范围都减小了。通过将力传感器测量值与校准的阈值进行比较，不稳定性检测算法可以识别超过 93%的自我诱发跌倒，假警率为 0%。
虽然机器人的顺应性和不稳定性识别仍有改进的空间，但该研究展示了将步态辅助技术引入家庭的第一步。我们希望机器人能够鼓励平衡受损的人群更多地参与日常生活活动，以提高他们的生活质量。未来的研究包括招募更多平衡困难的受试者，以进一步完善设备功能。
