Peripheral Autonomic Signals as Access Pathways for Individuals with Severe Disabilities: A Literature Appraisal

Blain, Stefanie; Chau, Tom; Mihailidis, Alex

doi:10.2174/1874943700801010027

Cited by 28 publications

(31 citation statements)

References 98 publications

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“…The remaining components of the model are the same as those in Figure 2. The most well-established method of EDA measurement entails the exosomatic detection of current (I) when a constant voltage (V) is applied between two electrodes [89]. Less commonly, a constant current will be applied while voltage is measured to quantify the resistance (R) between the two electrodes.…”

Section: Current Practicementioning

confidence: 99%

“…Typically the palms of the hands or the soles of the feet are the preferred locations [90]. EDRs can be interpreted as measures of physiological and psychological arousal, but they can be indicative of both negative and positive stimuli [89]. In clinical rehabilitation, electrodermal measurements may serve as a complementary access pathway to a motor-based switch [91] or brain-computer interface [92], an indicator of autonomic nervous system response to anxiety in children with autism spectrum disorders [93], and a quantitative measure of motor imagery abilities in individuals with spinal cord injuries [94], among other possibilities.…”

Section: Current Practicementioning

confidence: 99%

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E-textiles in Clinical Rehabilitation: A Scoping Review

2015

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Electronic textiles have potential for many practical uses in clinical rehabilitation. This scoping review appraises recent and emerging developments of textile-based sensors with applications to rehabilitation. Contributions published from 2009 to 2013 are appraised with a specific focus on the measured physiological or biomechanical phenomenon, current measurement practices, textile innovations, and their merits and limitations. While fabric-based signal quality and sensor integration have advanced considerably, overall system integration (including circuitry and power) has not been fully realized. Validation against clinical gold standards is inconsistent at best, and feasibility with clinical populations remains to be demonstrated. The overwhelming focus of research and development has been on remote sensing but the opportunity for textile-mediated feedback to the wearer remains unexplored. Recommendations for future research are provided.

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Section: Current Practicementioning

confidence: 99%

Section: Current Practicementioning

confidence: 99%

E-textiles in Clinical Rehabilitation: A Scoping Review

2015

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“…Polygraphy studies have shown that electrodermal reactions can be controlled via mental relaxation exercises [55]. The mental stimulation literature, in turn, has shown that mental imagery tasks, such as motor or music imagery, can be used to control several ANS signals with the degree of observed responses being proportional to the mental effort exerted by the subjects [28], [30], [32], [56].…”

Section: A Multimodal Mental State Classificationmentioning

confidence: 99%

“…This is motivated by previous research that has suggested that physiological responses such as changes to skin electrodermal activity [25], skin temperature [26], heart rate [27], respiration rates [28], and salivary pH [29] can be elicited by mental imagery tasks similar to those used to control NIRS-BCI systems. The reader is referred to [30] and the references therein for a more comprehensive review of volitional ANS control techniques. It is hypothesized that user intention can be better modeled once the two modalities are combined.…”

mentioning

confidence: 99%

Taking NIRS-BCIs Outside the Lab: Towards Achieving Robustness Against Environment Noise

Falk

Guirgis

Power

et al. 2011

IEEE Trans. Neural Syst. Rehabil. Eng.

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Abstract-This paper reported initial findings on the effects of environmental noise and auditory distractions on the performance of mental state classification based on near-infrared spectroscopy (NIRS) signals recorded from the prefrontal cortex. Characterization of the performance losses due to environmental factors could provide useful information for the future development of NIRS-based brain-computer interfaces that can be taken beyond controlled laboratory settings and into everyday environments. Experiments with a hidden Markov model-based classifier showed that while significant performance could be attained in silent conditions, only chance levels of sensitivity and specificity were obtained in noisy environments. In order to achieve robustness against environment noise, two strategies were proposed and evaluated. First, physiological responses harnessed from the autonomic nervous system were used as complementary information to NIRS signals. More specifically, four physiological signals (electrodermal activity, skin temperature, blood volume pulse, and respiration effort) were collected in synchrony with the NIRS signals as the user sat at rest and/or performed music imagery tasks. Second, an acoustic monitoring technique was proposed and used to detect startle noise events, as both the prefrontal cortex and ANS are known to involuntarily respond to auditory startle stimuli. Experiments with eight participants showed that with a startle noise compensation strategy in place, performance comparable to that observed in silent conditions could be recovered with the hybrid ANS-NIRS system. Index Terms-Ambient noise, autonomic nervous system, hidden Markov models, music imagery, near-infrared spectroscopy.

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“…A wide range of access pathways have been developed, from simple mechanical switches to sophisticated physiological ones. For a comprehensive review of emerging access technologies please see [1,2].…”

Section: Access Pathwaysmentioning

confidence: 99%

Mutual Information as a Measure of Contextual Effects on Single Switch Use

Memarian¹,

Venetsanopoulos²,

Chau

2009

TOREHJ

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We propose the use of mutual information as an objective means of measuring the impact of contextual factors on mechanical single switch usage. We show that common performance measures (e.g. sensitivity, specificity and response time) relating to switch use can be quantitatively unified within a mutual information measure. We exemplify the use of mutual information in the assessment of switch use in the presence of selected contextual factors. This information theoretic measure facilitates performance comparison amongst users and can potentially help in classification of contextual stimuli in terms of their impact (i.e. facilitating, barrier, neutral). Our examples with able-bodied participants and an individual with disability indicate that mutual information can be sensitive to changes in contextual factors. Mutual information may thus inform the design of individualized access technologies.

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Peripheral Autonomic Signals as Access Pathways for Individuals with Severe Disabilities: A Literature Appraisal

Cited by 28 publications

References 98 publications

E-textiles in Clinical Rehabilitation: A Scoping Review

E-textiles in Clinical Rehabilitation: A Scoping Review

Taking NIRS-BCIs Outside the Lab: Towards Achieving Robustness Against Environment Noise

Mutual Information as a Measure of Contextual Effects on Single Switch Use

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