Yes/No or Maybe—further evaluation of an interface for brain-injured individuals

Doherty, Eamon; Cockton, Gilbert; Bloor, Chris; Rizzo, Joann; Blondina, Bruce; Davis, Bruce A.

doi:10.1016/s0953-5438(02)00022-x

Cited by 14 publications

(14 citation statements)

References 3 publications

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“…As stated in Section 1.3, this channel is responsible for extracting the affective measures and cues based on the ACE scheme [18], [19], [20], [21], [22] (see Section 2.6). It should be noted that the interline of the electrodes of this channel is somehow perpendicular to the frontalis muscle fibers.…”

Section: Site Selection and Placement Of Electrodesmentioning

confidence: 99%

Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis

Rezazadeh

Firoozabadi

et al. 2012

IEEE Trans. Affective Comput.

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Abstract-The real-time adaptation between human and assistive devices can improve the quality of life for amputees, which, however, may be difficult to achieve since physical and mental states vary over time. This paper presents a co-adaptive humanmachine interface (HMI) that is developed to control virtual forearm prosthesis over a long period of operation. Direct physical performance measures for the requested tasks are calculated. Bioelectric signals are recorded using one pair of electrodes placed on the frontal face region of a user to extract the mental (affective) measures (the entropy of the alpha band of the forehead electroencephalography signals) while performing the tasks. By developing an effective algorithm, the proposed HMI can adapt itself to the mental states of a user, thus improving its usability. The quantitative results from 16 users (including an amputee) show that the proposed HMI achieved better physical performance measures in comparison with the traditional (nonadaptive) interface (p-value < 0:001). Furthermore, there is a high correlation (correlation coefficient < 0:9; p-value < :01) between the physical performance measures and self-report feedbacks based on the NASA TLX questionnaire. As a result, the proposed adaptive HMI outperformed a traditional HMI.

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Section: Site Selection and Placement Of Electrodesmentioning

confidence: 99%

Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis

Rezazadeh

Firoozabadi

et al. 2012

IEEE Trans. Affective Comput.

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“…Then he went on to develop a simple Yes/No communication interface [11][12][13]. Doherty's participants used the Cyberlink in their normal care settings and some were able to communicate with medical staff, their carers and family for the first time in years.…”

Section: Traumatic Brain Injury and Brain-body Interfacesmentioning

confidence: 99%

“…Doherty's participants used the Cyberlink in their normal care settings and some were able to communicate with medical staff, their carers and family for the first time in years. Doherty thus established the possibility of brain-body interaction for the brain-injured, resulting in a profound impact on two of his participants and their families [11,13]. …”

Section: Traumatic Brain Injury and Brain-body Interfacesmentioning

confidence: 99%

“…It may be the only usable aid for brain-injured nonverbal quadriplegic participants [20]. Previous research by the last two authors and Eamon Doherty using the Cyberlink has opened up an entirely new spectrum of assistive technologies [11][12][13][14][15][16], which are particularly appropriate for people with traumatic brain-injury, especially those who suffer from "locked-in" syndrome, and appear to be comatose but are actually sentient [9]. One such individual has become a very valuable contributor to research, yet his capabilities went unrecognised for many years [3,15,24].…”

mentioning

confidence: 99%

“…Doherty found that successful participation in research does contribute to the cognitive and neural rehabilitation for traumatic brain injury [11][12][13][14][15][16]. We therefore saw much value in seeking to extend the scope of brain-body interfaces, in terms of both the population who could use them and in terms of what (some) users could do with them.…”

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confidence: 99%

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Discrete acceleration and personalised tiling as brain?body interface paradigms for neurorehabilitation

Gnanayutham

Bloor

Cockton

2005

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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We present two studies that have advanced the design of brain-body interfaces for use in the rehabilitation of individuals with severe neurological impairment due to traumatic brain injury. We first developed and evaluated an adaptive cursor acceleration algorithm based on screen areas. This improved the initial design, but was too inflexible to let users make the most of their highly varied abilities. Only some individuals were well served by this adaptive interface. We therefore developed and evaluated an approach based on personalized tile layouts.The rationales for both designs are presented, along with details of their implementation. Evaluation studies for each are reported, which show that we have extended the user population who can use our interfaces relative to previous studies. We have also extended the usable functionality for some of our user group. We thus claim that personalized tiling with discrete acceleration has allowed us to extend the usable functionality of brain-body interfaces to a wider population with traumatic brain injury, thus creating new options for neurorehabiliation.

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Assistive Technology for People with Acquired Brain Injury

Rispoli

Machalicek

Lang

2014

Autism and Child Psychopathology Series

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Yes/No or Maybe—further evaluation of an interface for brain-injured individuals

Cited by 14 publications

References 3 publications

Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis

Co-Adaptive and Affective Human-Machine Interface for Improving Training Performances of Virtual Myoelectric Forearm Prosthesis

Discrete acceleration and personalised tiling as brain?body interface paradigms for neurorehabilitation

Assistive Technology for People with Acquired Brain Injury

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