Engineering study on the use of Head-Mounted display for Brain- Computer Interface

Andreev, Anton; Cattan, Grégoire; Congedo, M

doi:10.48550/arxiv.1906.12251

Cited by 2 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The lower latencies observed with the HMD setup than the LED screen setup suggested faster temporal dynamics for the immersive VR apparatus ( Iwama et al, 2022 ). Although this observation is consistent with findings in the literature ( Cattan et al, 2021 ), variations are particularly subject to protocols that rely on sending triggers for synchronization ( Wang et al, 2016 ; Lees et al, 2018 ) and specifications of the hardware apparatuses ( Rebenitsch and Owen, 2017 ; Cattan et al, 2018 ; Andreev et al, 2019 ; Wilson, 2023 ).…”

Section: Resultssupporting

confidence: 91%

See 1 more Smart Citation

CLET: Computation of Latencies in Event-related potential Triggers using photodiode on virtual reality apparatuses

Swami,

Gramann,

Vonstad

et al. 2023

Front. Hum. Neurosci.

View full text Add to dashboard Cite

To investigate event-related activity in human brain dynamics as measured with EEG, triggers must be incorporated to indicate the onset of events in the experimental protocol. Such triggers allow for the extraction of ERP, i.e., systematic electrophysiological responses to internal or external stimuli that must be extracted from the ongoing oscillatory activity by averaging several trials containing similar events. Due to the technical setup with separate hardware sending and recording triggers, the recorded data commonly involves latency differences between the transmitted and received triggers. The computation of these latencies is critical for shifting the epochs with respect to the triggers sent. Otherwise, timing differences can lead to a misinterpretation of the resulting ERPs. This study presents a methodical approach for the CLET using a photodiode on a non-immersive VR (i.e., LED screen) and an immersive VR (i.e., HMD). Two sets of algorithms are proposed to analyze the photodiode data. The experiment designed for this study involved the synchronization of EEG, EMG, PPG, photodiode sensors, and ten 3D MoCap cameras with a VR presentation platform (Unity). The average latency computed for LED screen data for a set of white and black stimuli was 121.98 ± 8.71 ms and 121.66 ± 8.80 ms, respectively. In contrast, the average latency computed for HMD data for the white and black stimuli sets was 82.80 ± 7.63 ms and 69.82 ± 5.52 ms. The codes for CLET and analysis, along with datasets, tables, and a tutorial video for using the codes, have been made publicly available.

show abstract

Section: Resultssupporting

confidence: 91%

“…The shorter latencies observed in the HMD setup compared to the LED screen setup can likely be attributed to the hardware characteristics of the display technology, which could facilitate faster triggering and data transmission ( Cattan et al, 2018 ; Andreev et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

CLET: Computation of Latencies in Event-related potential Triggers using photodiode on virtual reality apparatuses

Swami,

Gramann,

Vonstad

et al. 2023

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…3.4). Four continuous model instances are being used in this project, with a separate instance for each gesture (1)(2)(3)(4). This is both because the EMG information for each gesture is very different/unique and because this model is used for the regression of a particular input (gesture), not the classification of different gestural states.…”

Section: Machine Learningmentioning

confidence: 99%

“…Recent technological advances and the improved affordability of VR equipment have allowed VR to be useful for education [7], military training operations [5] and music instrument performance [15]. Due to such promise, contemporary research has investigated the use of biometric EEG data, with a commercial Head Mounted Display (HMD) to create a Brain-Computer Interface (BCI) [1,16]. However, other forms of biometric data more significant for music practice can be used within VR to compose and perform music -namely, EMG.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Classifying Biometric Data for Musical Interaction Within Virtual Reality

Rhodes

Allmendinger

Climent

2022

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Since 2015, commercial gestural interfaces have widened accessibility for researchers and artists to use novel Electromyographic (EMG) biometric data. EMG data measures musclar amplitude and allows us to enhance Human-Computer Interaction (HCI) through providing natural gestural interaction with digital media. Virtual Reality (VR) is an immersive technology capable of simulating the real world and abstractions of it. However, current commercial VR technology is not equipped to process and use biometric information. Using biometrics within VR allows for better gestural detailing and use of complex custom gestures, such as those found within instrumental music performance, compared to using optical sensors for gesture recognition in current commercial VR equipment. However, EMG data is complex and machine learning must be used to employ it. This study uses a Myo armband to classify four custom gestures in Wekinator and observe their prediction accuracies and representations (including or omitting signal onset) to compose music within VR. Results show that specific regression and classification models, according to gesture representation type, are the most accurate when classifying four music gestures for advanced music HCI in VR. We apply and record our results, showing that EMG biometrics are promising for future interactive music composition systems in VR.

show abstract

Engineering study on the use of Head-Mounted display for Brain- Computer Interface

Cited by 2 publications

References 0 publications

CLET: Computation of Latencies in Event-related potential Triggers using photodiode on virtual reality apparatuses

CLET: Computation of Latencies in Event-related potential Triggers using photodiode on virtual reality apparatuses

Classifying Biometric Data for Musical Interaction Within Virtual Reality

Contact Info

Product

Resources

About