Stroke, spinal cord injury and muscular atrophy are just few examples of diseases leading to persistent hand impairment. No matter the cause, the inability to use the affected hand in activities of daily living will affect independence and quality of life. Wearable robotic devices can support the use of the impaired limb in activities of daily living, and provide at-home rehabilitation training. In collaboration with the groups of Prof. Jumpei Arata at Kyushu University, Japan, and Gregory Fischer at Worcester Polytechnic Institute, USA, we have developed a highly compact and lightweight hand exoskeleton.
Our exoskeleton aims to assist patients in grasping tasks during physiotherapy and in activities of daily living such as eating or grooming. Various grasp types, intuitive control based on electromyography (Ryser et al., 2017) and numerous usability features should increase the independence of the user. The current prototype, RELab tenoexo, is fully wearable and consists of a lightweight hand module (148 g) as well as an actuation box including motors, power source and controllers (720 g), all located in a compact backpack. tenoexo’s remote actuation system (Hofmann et al., 2018) and its compliant 3-layered sliding spring mechanism (Arata et al., 2013) ensure safe operation and inherent adaptation to the shape of the grasped objects. The palmar side of the hand is minimally covered to allow for natural somatosensory feedback during object manipulation. The actuated thumb module allows for both opposition and lateral grasps. tenoexo is fabricated to a large extent by 3D-printing technology. With an underlying automatic tailoring algorithm it can be adapted to the individual user within a few minutes. The maximal fingertip force of 4.5 N per finger allows for grasping and lifting of most everyday objects, up to 0.5-liter water bottles.
Our current focus is on the evaluation of tenoexo with several individuals suffering from stroke or spinal cord injury and exploring its potential as both assistive and therapeutic device in these populations. In related projects, we are investigating intention detection through functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) to allow for cortically-triggered assistance. Our vision is to realize a thought-controlled robotic hand exoskeleton for upper limb therapy and assistance in the clinic and at home.