Exoskeletons for rehabilitation can help enhance motor recovery in individuals suffering from neurological disorders. Precision in movement execution, especially in arm rehabilitation, is crucial to prevent maladaptive plasticity. However, current exoskeletons, while providing arm support, often lack the necessary 3D feedback capabilities to show how well rehabilitation exercises are being performed. This reduces therapist acceptance and patients' performance. Augmented Reality technologies offer promising solutions for feedback and gaming systems in rehabilitation. In this work, we leverage HoloLens 2 with its advanced hand-tracking system to develop an application for personalized rehabilitation. Our application generates custom holographic trajectories based on existing databases or therapists' demonstrations, represented as 3D tunnels. Such trajectories can be superimposed on the real training environment. They serve as a guide to the users and, thanks to colour-coded real-time feedback, indicate their performance. To assess the efficacy of the application in improving kinematic precision, we tested it with 15 healthy subjects. Comparing user tracking capabilities with and without the use of our feedback system in executing 4 different exercises, we observed significant differences, demonstrating that our application leads to improved kinematic performance. 12 clinicians tested our system and positively evaluated its usability (System Usability Scale score of 67.7) and acceptability (4.4 out of 5 in the 'Willingness to Use' category in the relative Technology Acceptance Model). The results from the tests on healthy participants and the feedback from clinicians encourage further exploration of our framework, to verify its potential in supporting arm rehabilitation for individuals with neurological disorders.

翻译：康复外骨骼有助于促进神经系统疾病患者的运动功能恢复。动作执行的精确性——尤其是在手臂康复中——对于防止适应不良性神经可塑性至关重要。然而，当前的外骨骼虽能提供手臂支撑，却往往缺乏必要的三维反馈能力来显示康复训练的完成质量，这降低了治疗师的接受度和患者的训练表现。增强现实技术为康复领域的反馈与游戏化系统提供了前景广阔的解决方案。本研究利用HoloLens 2及其先进的手部追踪系统，开发了一款个性化康复应用。该应用基于现有数据库或治疗师示范动作生成定制化的全息轨迹（以三维隧道形式呈现），可叠加于真实训练环境中。这些轨迹既能指导用户训练，又能通过颜色编码的实时反馈显示其训练表现。为评估该应用在提升运动学精度方面的效能，我们对15名健康受试者进行了测试。通过比较使用与不使用本反馈系统执行4种不同训练任务时的用户追踪能力，我们观察到显著差异，证明本应用能有效提升运动学表现。12名临床医师测试了本系统，对其可用性（系统可用性量表得分67.7）和接受度（相关技术接受模型中"使用意愿"维度评分4.4/5）给予积极评价。健康受试者的测试结果与临床医师的反馈，共同支持对本框架开展进一步探索，以验证其在辅助神经系统疾病患者手臂康复方面的潜力。