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. 2018 Oct 11:12:67.
doi: 10.3389/fnbot.2018.00067. eCollection 2018.

Bio-Cooperative Approach for the Human-in-the-Loop Control of an End-Effector Rehabilitation Robot

Francesco Scotto di Luzio  1 , Davide Simonetti  1 , Francesca Cordella  1 , Sandra Miccinilli  2 , Silvia Sterzi  2 , Francesco Draicchio  3 , Loredana Zollo  1
Affiliations

Bio-Cooperative Approach for the Human-in-the-Loop Control of an End-Effector Rehabilitation Robot

Francesco Scotto di Luzio et al. Front Neurorobot. .

Abstract

The design of patient-tailored rehabilitative protocols represents one of the crucial factors that influence motor recovery mechanisms, such as neuroplasticity. This approach, including the patient in the control loop and characterized by a control strategy adaptable to the user's requirements, is expected to significantly improve functional recovery in robot-aided rehabilitation. In this paper, a novel 3D bio-cooperative robotic platform is developed. A new arm-weight support system is included into an operational robotic platform for 3D upper limb robot-aided rehabilitation. The robotic platform is capable of adapting therapy characteristics to specific patient needs, thanks to biomechanical and physiological measurements, and thus closing the subject in the control loop. The level of arm-weight support and the level of the assistance provided by the end-effector robot are varied on the basis of muscular fatigue and biomechanical indicators. An assistance-as-needed approach is applied to provide the appropriate amount of assistance. The proposed platform has been experimentally validated on 10 healthy subjects; they performed 3D point-to-point tasks in two different conditions, i.e., with and without assistance-as-needed. The results have demonstrated the capability of the proposed system to properly adapt to real needs of the patients. Moreover, the provided assistance was shown to reduce the muscular fatigue without negatively influencing motion execution.

Keywords: arm-gravity support; biocooperative control; human-in-the-loop; muscle activation; upper limb robot-aided rehabilitation.

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Figures

Figure 1
Figure 1
Mechanical structure of the adaptive arm-gravity support system: 1 Frame, 2 Support bar, 3 Pulleys, 4 Cable, 5 7-DoF robot arm Kuka LWR4+, 6 Maxon EC-max 40 motor, 7 Encoder, 8 Ergonomic backing for the arm.
Figure 2
Figure 2
Block scheme of the proposed closed-loop architecture.
Figure 3
Figure 3
The proposed 3D bio-cooperative robotic platform. (A) Detail of M-IMU and sEMG sensors used with arm-weight support; (B) Arm-weight support with the whole platform: subject interacts with robotic arm and arm-gravity support.
Figure 4
Figure 4
Task duration without and with assistance-as-needed.
Figure 5
Figure 5
Lkr and Lt without and with assistance-as-needed.
Figure 6
Figure 6
Mean sEMG activity (normalized) and standard deviation during the execution of task without assistance-as-needed.
Figure 7
Figure 7
Mean sEMG activity (normalized) and standard deviation during the execution of task with assistance-as-needed.
Figure 8
Figure 8
Ls without and with assistance-as-needed.
Figure 9
Figure 9
Desired crankshaft position qd and desired torque τd of the arm-gravity support for a sample subject with a compensation of 50% of the τmax necessary to completely support subject arm.
See this image and copyright information in PMC

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