Detection of Movement Intention for Operating Methods of Serious Games

Abstract

In many post-stroke cases, patients show dysfunctions in movement, cognition, sense, and language, depending on the damaged area of the brain. Active and repetitive physical rehabilitation centered on the stroke-affected side is essential for effective and rapid neurological recovery of upper extremity dysfunction due to hemiplegia. A symmetric upper extremity trainer is utilized to assist the patient body, depending upon the degree of hemiplegia. In this study, we developed a novel balance handle as a symmetric upper extremity trainer capable of extension, flexion, pronation, and supination of the upper extremity. We collected the surface electromyogram (sEMG) signal data while the subjects were playing a serious game and recorded the electroencephalogram (EEG) signal data while the subjects were performing basic movements with the balance handle, to analyze the effectiveness of the device as an assistive tool for rehabilitation. The triceps brachii were activated during the extension movements, whereas the biceps brachii and deltoid muscles were activated during the flexion movements. With the balance handle, the peak event-related desynchronization (ERD) values were relatively lower while showing higher peak event-related synchronization (ERS) values compared to other types of operating methods, such as hand gripping and gamepad operation. Movement intention of tilting the balance handle for the α and β waves was clearly distinguished from the other tasks. These data demonstrated the potential of various applications using the developed proof-of-concept upper extremity trainer to bring out an excellent rehabilitative effect not only through muscle growth but also via identification of large movement intentions inducing brain activation exercise.

Combined Use of EMG and EEG Techniques for Neuromotor Assessment in Rehabilitative Applications: A Systematic Review

“…The distribution of papers in the categories is shown in a pie chart in Figure 4. Study of the cortico-muscular coupling (1) during motor tasks [37][38][39][40][41] and (2) with electrical stimulation [42][43][44][45][46] Investigation of the effects of exoskeleton on functional connectivity [47][48][49] Investigation of the effects of visual feedback [50,51] Detection of movement intention [52,53] Study of the interhemispheric interaction with TMS [54] Study of a neurophysiological marker of stress [55] Study of slow cortical potentials in stroke [56] Study of correlation between lower back pain and altered postural stabilization [57] Test new rehabilitation paradigm [34,[58][59][60][61][62] Investigation of the efficacy of BMI [63] and EEG feedback [64] Table 1. Type of study and aim.…”

“…The efficacy of visual feedback was assessed to explore novel rehabilitation paradigms [50,51]. Two studies only [52,53] were interested in detecting movement intention coupled with EEG and EMG recordings. Other works investigated specific parameters typical of each study: Palmer et al [54] studied the interhemispheric interaction using transcranial stimulation, Vladimirov et al [55] searched neurophysiological markers of stress, Yilmaz et al [56] investigated slow cortical potentials in stroke patients, and Jacobs et al [57] studied the correlation between low back pain and postural stabilization.…”

“…Parkinson disease: 40-80 [76]; Cerebral palsy: 5-19 [34]; Spinal cord injury: 32.5 ± 6.2 [38], 26-38 [63], 32 ± 6 [65], 43.5 ± 12.4 [53]; Writer's cramp: 67 [64]; Low back pain: 39.2 ± 6.33 [57]; Mixed injuries and diseases: 33-54 [73], 60-80 [59]; Facial palsy: 23 [74]; MCI: n.a. [85]; Cardiovascular diseases: 56.3 ± 1.0 [55] Nr of subjects ≤10 6 [37], 5 [32], 6 [34], 3 + 4 [58], 6 [61], 1 [84], 8 [63], 10 [72], 2 [62], 1 [64], 7 [66], 5 [47], 8 [67], 7 [52], 10 [33], 1 [74], 5 + 5 [40] Torso: [57]; Face: [74]; Neck: [68] 3.3.1. Cohorts of Subjects…”

“…Bartur and colleagues [50] employed mirror visual feedback in the rehabilitation setup for hemiparetic stroke patients. The effectiveness of a novel balance handle was assessed with arm movements [52].…”

“…Mirror visual feedback [50] Wrist movements [69,84]; wrist movements + visual feedback [73] Elbow movements [38]; elbow movements + visual feedback [65] Arm movements [37,57,70,71,87,88]; arm movements + auditory feedback [82]; arm movements + balance handle [52] Hand movements [40,67,83,86]; hand movements + motor imagery + auditory/smelling stimulus [85]; hand movements + audiovisual feedback [56]; hand movements + biofeedback [64] Leg movements [53] Motor imagery swallow and tongue protrusion [68] Respiratory movements [55] Oculus rift [74] Robotic assistance Exoskeleton lower limb + virtual reality [34]; exoskeleton lower limb + virtual reality + BMI [63]; exoskeleton lower limb + walking [47,48,80]; exoskeleton lower limb + treadmill [49] Robotic end effector upper limb [32,33,58,59] Robotic mirror therapy upper limb [60] Hand mobilizer exoskeleton [39,61,62]; hand mobilizer exoskeleton + motor imagery [66] Ankle mobilizer [41] Peripheral electrical stimulation FES + hand movements [43...…”