513 research outputs found

    A BIONIC EYEBLINK: MANAGEMENT OF FACIAL PALSY

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    This thesis highlights the current gold-standard surgical procedures for the rehabilitation of mimicry in individuals with facial paralysis and explores the potential application of functional electrical stimulation (FES) as a novel treatment restoring the face mimicry. Closed-loop facial pacing represents an innovative solution for prosthetically assisted movements. In particular, blinking is typically symmetrical, enabling healthy eye blink on one side of the face to serve as a trigger to pace assisted blinks on the contralateral side, in case of unilateral peripheral facial palsy. The goals of this research are developing an eyeblink detection system and advancing the understanding of performing surface FES of the facial nerve in order to elicit artificial eyeblinks. The application of a biomimetic device to individuals with acute reversible facial palsy would provide immediate restoration of the periocular function and could be used until either the patient recovers sufficient function to no longer require assistance for eye closure, or the decision is made to proceed with further surgery

    A multi-artifact EEG denoising by frequency-based deep learning

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    Electroencephalographic (EEG) signals are fundamental to neuroscience research and clinical applications such as brain-computer interfaces and neurological disorder diagnosis. These signals are typically a combination of neurological activity and noise, originating from various sources, including physiological artifacts like ocular and muscular movements. Under this setting, we tackle the challenge of distinguishing neurological activity from noise-related sources. We develop a novel EEG denoising model that operates in the frequency domain, leveraging prior knowledge about noise spectral features to adaptively compute optimal convolutional filters for noise separation. The model is trained to learn an empirical relationship connecting the spectral characteristics of noise and noisy signal to a non-linear transformation which allows signal denoising. Performance evaluation on the EEGdenoiseNet dataset shows that the proposed model achieves optimal results according to both temporal and spectral metrics. The model is found to remove physiological artifacts from input EEG data, thus achieving effective EEG denoising. Indeed, the model performance either matches or outperforms that achieved by benchmark models, proving to effectively remove both muscle and ocular artifacts without the need to perform any training on the particular type of artifact.Comment: Accepted at the Italian Workshop on Artificial Intelligence for Human-Machine Interaction (AIxHMI 2023), November 06, 2023, Rome, Ital

    Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

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    Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform

    Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

    Get PDF
    Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform

    Psychophysiological measurements in programming task:guidelines for conducting EMG research

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    Abstract. Programming languages have been studied and developed throughout history of programming. There are lots of different programming languages that are being used in software development, but only core languages are taught in Universities. Programming languages usually have their own syntax, which may differ greatly from each other. Using different programming languages for same task may provoke different emotions in programmers, depending their knowledge on the language. Research on programming and programming languages have generally focused on technical and exterior aspects. More recently, there has been some research on the programmers and their emotions during the programming tasks. This master’s thesis focuses on latter and aims to provide new information of programmers experienced emotions during the programming tasks by using EMG-recordings. This master thesis’ main study focus is in psychophysiology, which combines psychology to physiological research, by finding correlation between physiological activity and emotional phenomenon. This study assessed university students experienced emotions when conducting programming tasks with C and Python programming languages. EMG measurement device was used on the test participants to record signal data from facial based muscles for smiling and frowning activity, which are linked to positive and negative emotions. This study’s results showed small differences with emotional experiences during the programming tasks, but the overall results were not statistically significant. Therefore, more research on this topic is needed for more consistent results. Additionally, this research has provided guidelines on how EMG studies are conducted on laboratory setting and suggestions for future studies

    Safety and pain in electrodiagnostic studies

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    Discomfort is an unavoidable part of electrodiagnostic (EDX) studies. The most readily modifiable mediator of electromyography (EMG)‐associated pain is muscle selection. Interventions that may reduce pain include vapocoolant spray, ibuprofen, and techniques such as slapping or stretching the skin. Needlestick injuries to health care workers carry the risk of transmitting bloodborne illnesses, but other infectious complications of EDX studies are very rare. EMG probably contributes to asymptomatic hemorrhage in approximately 1% of patients, but clinically significant bleeding has only been reported a few times. Therapeutic anticoagulation does not significantly increase this risk. With standard procedures, there have been no reports of patients developing cardiac arrhythmia from nerve conduction studies. No special precautions are necessary in patients with implantable cardiac devices or intravenous lines. There is a small risk of pneumothorax associated with EMG of the diaphragm and chest wall muscles. Several techniques have been suggested to improve the safety of diaphragm EMG. Muscle Nerve 55: 149–159, 2017Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/136014/1/mus25421_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/136014/2/mus25421.pd

    Non-intrusive Physiological Monitoring for Affective Sensing of Computer Users

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    The effect of electronic word of mouth communication on purchase intention moderate by trust: a case online consumer of Bahawalpur Pakistan

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    The aim of this study is concerned with improving the previous research finding complete filling the research gaps and introducing the e-WOM on purchase intention and brand trust as a moderator between the e-WOM, and purchase intention an online user in Bahawalpur city Pakistan, therefore this study was a focus at linking the research gap of previous literature of past study based on individual awareness from the real-life experience. we collected data from the online user of the Bahawalpur Pakistan. In this study convenience sampling has been used to collect data and instruments of this study adopted from the previous study. The quantitative research methodology used to collect data, survey method was used to assemble data for this study, 300 questionnaire were distributed in Bahawalpur City due to the ease, reliability, and simplicity, effective recovery rate of 67% as a result 202 valid response was obtained for the effect of e-WOM on purchase intention and moderator analysis has been performed. Hypotheses of this research are analyzed by using Structural Equation Modeling (SEM) based on Partial Least Square (PLS). The result of this research is e-WOM significantly positive effect on purchase intention and moderator role of trust significantly affects the relationship between e-WOM, and purchase intention. The addition of brand trust in the model has contributed to the explanatory power, some studied was conduct on brand trust as a moderator and this study has contributed to the literature in this favor. significantly this study focused on current marketing research. Unlike past studies focused on western context, this study has extended the regional literature on e-WOM, and purchase intention to be intergrading in Bahawalpur Pakistan context. Lastly, future studies are recommended to examine the effect of trust in other countries allow for the comparison of the findings
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