Details

Autor(en) / Beteiligte

• Sangwoo Park
• Meeker, Cassie
• Weber, Lynne M.
• Bishop, Lauri
• Stein, Joel
• Ciocarlie, Matei

Titel

Multimodal Sensing and Interaction for a Robotic Hand Orthosis

Ist Teil von

• IEEE robotics and automation letters, 2019-04, Vol.4 (2), p.315-322

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2019

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• Wearable robotic hand rehabilitation devices can allow greater freedom and flexibility than their workstation-like counterparts. However, the field is generally lacking effective methods by which the user can operate the device: such controls must be effective, intuitive, and robust to the wide range of possible impairment patterns. Even when focusing on a specific condition, such as stroke, the variety of encountered upper limb impairment patterns means that a single sensing modality, such as electromyography (EMG), might not be sufficient to enable controls for a broad range of users. To address this significant gap, we introduce a multimodal sensing and interaction paradigm for an active hand orthosis. In our proof-of-concept implementation, EMG is complemented by other sensing modalities, such as finger bend and contact pressure sensors. We propose multimodal interaction methods that utilize this sensory data as input and show they can enable tasks for stroke survivors who exhibit different impairment patterns. We believe that robotic hand orthoses developed as multimodal sensory platforms with help address some of the key challenges in physical interaction with the user.