BKI: Brain Kinect Interface, a new hybrid BCI for rehabilitation

Muñoz, John Edison; Henao, Oscar; Lopez, J.F.; Villada, Julian F.

doi:10.1007/978-3-658-02897-8_18

Cited by 10 publications

(7 citation statements)

References 12 publications

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“…Our work, the BKI approach is a multimodal interface that aims to consolidate a neural engineering real-time processing system based on EEG and Kinematic signals [13]. In general terms, the diseases and injuries of the central nervous system (CNS) leading to sensory-motor impairment are the problem to solve.…”

Section: Bki: Brain Kinect Interfacementioning

confidence: 99%

BCI and motion capture technologies for rehabilitation based on videogames

Muñoz

Chavarriaga

Villada

et al. 2014

IEEE Global Humanitarian Technology Conference (GHTC 2014)

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this paper presents a cost-effective rehabilitation system based on videogames and multi modal recordings of physiological signals. The system targets patients with sensory motor impairments resulting from lesions of the central nervous system (e.g., due to stroke or traumatic injuries). It relies on a wireless low-cost hybrid interface combining a consumer-level electroencephalographic (EEG) device and the Kinect sensor to record the motion capture information. Thus providing quantitative physiological measures to support medical evaluations and improve the personalization of health service. Furthermore, through the design of specialized videogames for rehabilitation, this approach aim at increasing the patient's motivation, potentially improving the service quality and the recovery process. The system is currently being used in a rehabilitation center in Colombia by patients with upper limb paralysis and balance disorders after stroke or traumaticuries.Initial results show significant improvements in the mobility of affected joints, improved adherence to treatments by patients, and high acceptability by therapists and end-users.

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Section: Bki: Brain Kinect Interfacementioning

confidence: 99%

BCI and motion capture technologies for rehabilitation based on videogames

Muñoz

Chavarriaga

Villada

et al. 2014

IEEE Global Humanitarian Technology Conference (GHTC 2014)

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“…The signals are taken through the low cost BCI system MindWave and processed using the open source software OpenViBe. Then also the BKI [5] system was used in order to provide tools for the post-processing of the MoCap data using specialized software designed for this purpose. The development of this solution followed the methodology proposed by Pamela Kato [9], in where seven steps are mentioned: a) agree with clarity and objectivity the problem to solve, b) agree on a theory or theories of how to solve it, c) find candidate measures, d) provide a structure for reaching research goals, e) start thinking about the research design, f) engage the target group, g) consider issues of safety.…”

Section: Standing Balance In Hemiparetic Stroke Survivorsmentioning

confidence: 99%

“…These hybrid BCIs (hBCI) exploit a combination of multiple signals including at least one BCI channel [4]. The convergence between signals from BCI systems with other biosignals, for instance, electromyographic data (EMG) or particular biomechanical signals obtained from motion capture (MoCap) systems [5], can allow a more stable and durable control of an application or device.. Pfurtscheller and colleagues have proposed four performance criteria to be fulfilled by the hBCI systems [4]: a) it must provide volitional control, b) it must rely on brain signals, c) it must provide feedback, and d) it must work online. All of these criteria equally apply to their use in videogames for health.…”

Section: Introductionmentioning

confidence: 99%

Application of hybrid BCI and exergames for balance rehabilitation after stroke

Muñoz

Chavarriaga²,

Lopez

2014

Proceedings of the 11th Conference on Advances in Computer Entertainment Technology

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This paper proposes the hybridization between two types of videogames (VG) that can be complementary in motor restoration tasks: the VG based on motion capture systems and the VG based on brain computer interfaces. This hybrid system allow the interaction inside of a VG created for the rehabilitation of standing balance in hemiparetic stroke patients through of movements and modulated mental intentions. The Brain Kinect Interface (BKI) is shown as a tool not only for improve the immersivity in serious VG for health, but as an instrumental arrangement for recording and analyzing of motion capture signals and electroencephalographic (EEG) signals recorded from the low cost sensors in order to improve the objectivity in analyzing motor recovery process.

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“…2. Shows Kinect's three dimensions coordinate system [22] In this study, KSCC algorithm [23] is utilized. The KSCC calibrates positions of all detected joints by transforming all positions to the initial center coordination.…”

Section: Disadvantagesmentioning

confidence: 99%

Multi kinect cameras setup for skeleton based action recognition

Phonsing

Laoarphakun

Thainimit

et al. 2015

2015 6th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES)

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In this research, we investigated and discussed several camera setup methods from different perspectives in order to exhibit advantages and shortcomings, as well as to reveal potentials of other camera setups in terms of image acquisition for action recognition system. Stability and accuracy of tracked skeletons of 10 actions from different views of camera settings are investigated. Experimental results indicates consistency of estimated skeleton lengths regardless of orientation placement of Kinect cameras. Accuracy of estimated skeleton data is less on actions with occluding body parts.

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BKI: Brain Kinect Interface, a new hybrid BCI for rehabilitation

Cited by 10 publications

References 12 publications

BCI and motion capture technologies for rehabilitation based on videogames

BCI and motion capture technologies for rehabilitation based on videogames

Application of hybrid BCI and exergames for balance rehabilitation after stroke

Multi kinect cameras setup for skeleton based action recognition

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