Development of a system based on 3D vision, interactive virtual environments, ergonometric signals and a humanoid for stroke rehabilitation

Zannatha, Juan Manuel Ibarra; Tamayo, Alejandro J. Malo; Sánchez, Ángel David Gómez; Delgado, Jorge Enrique Lavín; Cheu, Luis Eduardo Rodríguez; Arévalo, Wilson Alexander Sierra

doi:10.1016/j.cmpb.2013.04.021

Cited by 66 publications

(23 citation statements)

References 14 publications

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“…These facts led to the establishment of a new research field known as home based rehabilitation, as a complementary tool for therapeutic sessions. Furthermore, a new rehabilitation approach, known as exergames [3,4,5,6,7,8,9,10,11,12,13,14,15], has been proposed to help motivate patients while performing their rehabilitation tasks at home. This new concept incorporates games into the rehabilitation process, to add a motivational and challenging aspect to these programs.…”

Section: Introductionmentioning

confidence: 99%

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

Sensors

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Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject’s movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

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Section: Introductionmentioning

confidence: 99%

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

Sensors

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“…Beyond helping with activities of daily living, the possibility of fostering positive emotions creates several potential applications in rehabilitation and care for emerging robots (Diehl et al, 2012;Zannatha et al, 2013). Future work might compare user satisfaction with a human actuator.…”

Section: Discussionmentioning

confidence: 99%

Reaching and grasping a glass of water by locked-in ALS patients through a BCI-controlled humanoid robot

Spataro¹,

Sorbello²,

Tramonte³

et al. 2015

Journal of the Neurological Sciences

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Locked-in Amyotrophic Lateral Sclerosis (ALS) patients are fully dependent on caregivers for any daily need. At this stage, basic communication and environmental control may not be possible even with commonly used augmentative and alternative communication devices. Brain Computer Interface (BCI) technology allows users to modulate brain activity for communication and control of machines and devices, without requiring a motor control. In the last several years, numerous articles have described how persons with ALS could effectively use BCIs for different goals, usually spelling. In the present study, locked-in ALS patients used a BCI system to directly control the humanoid robot NAO (Aldebaran Robotics, France) with the aim of reaching and grasping a glass of water. Four ALS patients and four healthy controls were recruited and trained to operate this humanoid robot through a P300-based BCI. A few minutes training was sufficient to efficiently operate the system in different environments. Three out of the four ALS patients and all controls successfully performed the task with a high level of accuracy. These results suggest that BCI-operated robots can be used by locked-in ALS patients as an artificial alter-ego, the machine being able to move, speak and act in his/her place.

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“…The movements were monitored using wearable sensors and the video recordings were collected for evaluation of therapists. Zannatha et al presented a stroke rehabilitation system for upper limbs using Kinect, an interactive virtual environment, a humanoid robot and devices producing ergonometric signals [10]. The system architecture they created allows to integrate monitoring programs to evaluate the progress of a patient by a human.…”

Section: Related Workmentioning

confidence: 98%

Auto-evaluation of motion imitation in a child-robot imitation game for upper arm rehabilitation

Özgür

Siyli

Salah

2014

The 23rd IEEE International Symposium on Robot and Human Interactive Communication

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The purpose of this study is fusing play-like child robot interaction with physiotherapy in order to achieve upper arm rehabilitation by motivating the child. The proposed system is not intended to substitute for the physiotherapist, but to assist them in their therapeutic tasks by encouraging the child's participation in the activity. Recognizing the imitation performance of the child and supporting him/her with feedback for drawing the child's attention and motivating the child to imitate the robot is crucial. This study concentrates on automatically evaluating the upper body actions of the child during an imitation based physical therapy. For quantifying the performance of the child, two measures were considered: Range of Motion (RoM) and Dynamic Time Warping (DTW) distance. In our initial experiments, eight healthy children were asked to stand in front of a Kinect sensor and to mimic the actions of the humanoid robot Nao, which consist of shoulder abduction, shoulder vertical flexion&extension and elbow flexion. The proposed evaluation measure is verified as a reliable measurement according to Intraclass Correlation Coefficient (ICC) through comparison with evaluations of five physiotherapists as ground truth. The degree of consistency among our ratings and the physiotherapist ratings is between %76 and %96 for different motions.

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Development of a system based on 3D vision, interactive virtual environments, ergonometric signals and a humanoid for stroke rehabilitation

Cited by 66 publications

References 14 publications

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Reaching and grasping a glass of water by locked-in ALS patients through a BCI-controlled humanoid robot

Auto-evaluation of motion imitation in a child-robot imitation game for upper arm rehabilitation

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