Human arm joints reconstruction algorithm in rehabilitation therapies assisted by end-effector robotic devices

• DOI: 10.1186/s12984-018-0348-0
• Publication Date: 2018-02-20T02:25:42Z
• Authors: Arturo Bertomeu-M...; Andrea Blanco; Francisco J. Badesa; Juan A. Barios; Loredana Zollo; Nicolas Garcia-Ar...
• Keywords: Robot end effector

End-effector robots are commonly used in robot-assisted neuro-rehabilitation therapies for upper limbs where the patient's hand can be easily attached to a splint. Nevertheless, they not able estimate and control kinematic configuration of limb during therapy. However, Range Motion (ROM) together with clinical assessment scales offers comprehensive therapist. Our aim is present robust stable reconstruction algorithm accurately measure joints using only an accelerometer placed onto arm. The proposed based on inverse augmented Jaciobian as (Papaleo, et al., Med Biol Eng Comput 53(9):815–28, 2015). estimation elbow joint location performed through computation rotation measured by arm movement, making more against shoulder movements. Furthermore, we method compute initial necessary start integration method, protocol manually forearm lengths, position estimation. An optoelectronic system was test accuracy whilst healthy subjects were performing movements holding end effector seven Degrees Freedom (DoF) robot. In addition, previous algorithms studied therapy assisted 'PUPArm' planar robot three post-stroke patients. reports Root Mean Square Error (RMSE) 2.13cm 1.89cm wrist high correlation. These errors lead RMSE about 3.5 degrees (mean joints) correlation all respect real acquired system. Then, both reveal instability when movement appear due inevitable trunk compensation human end-effector robots. implemented followed environment without systems one Thus, ROM perfectly determined could become objective parameter assessment.