Gamma EEG Correlates of Haptic Preferences for a Dial Interface

Consumers often develop preferences toward consumer electronics based not only on the visual appearance of a product, but also on its haptic interface. If consumers express a strong haptic preference for a consumer electronic product, they are more likely to purchase it. Hence, it is important to understand how consumers' haptic preference for consumer electronics is formed. Conventional paper-based methods may not provide sufficient information for this purpose, because they provide post-event (i.e., after haptic experience) and environment-dependent (i.e., depending on the manner of asking questions, the person asking the questions, and so on.) data. Therefore, the present study investigated haptic preferences for consumer electronics using neural responses during haptic experiences, which provide the advantage of observing changes while the user is manipulating the product and obtaining environment-independent data. We measured neural responses using non-invasive electroencephalography (EEG). Eighteen volunteers participated in the study and manipulated a haptic dial knob that generates four different haptic profiles; during the manipulation, their EEG signals were recorded. After experiencing different haptic profiles, participants reported their level of preference for each profile. The analysis of EEG revealed that frontal gamma oscillations correlate with the level of haptic preferences, with oscillations becoming stronger with increasing haptic preference. The highest correlation between frontal gamma power and haptic preference was found in the early period of the dial task. Therefore, the frontal gamma oscillation of the EEG may represent a neural correlate of the haptic preference and provides a neural basis for understanding this preference in relation to consumer electronics

Neural Activations Associated With Friction Stimulation on Touch-Screen Devices

Tactile sensation largely influences human perception, for instance when using a mobile device or a touch screen. Active touch, which involves tactile and proprioceptive sensing under the control of movement, is the dominant tactile exploration mechanism compared to passive touch (being touched). This paper investigates the role of friction stimulation objectively and quantitatively in active touch tasks, in a real human-computer interaction on a touch-screen device. In this study, 24 participants completed an active touch task involved stroking the virtual strings of a guitar on a touch-screen device while recording the electroencephalography (EEG) signal. Statistically significant differences in beta and gamma oscillations in the middle frontal and parietal areas at the late period of the active touch task are found. Furthermore, stronger beta event-related desynchronization (ERD) and rebound in the presence of friction stimulation in the contralateral parietal area are observed. However, in the ipsilateral parietal area, there is a difference in beta oscillation only at the late period of the motor task. As for implicit emotion communication, a significant increase in emotional responses for valence, arousal, dominance, and satisfaction is observed when the friction stimulation is applied. It is argued that the friction stimulation felt by the participants' fingertip in a touch-screen device further induces cognitive processing compared to the case when no friction stimulation is applied. This study provides objective and quantitative evidence that friction stimulation is able to affect the bottom-up sensation and cognitive processing

Interbrain Synchrony During MIT

Preprocessed / epoched EEG data and Behavioral data. Copyright 2022 Wanjoo Park, New York University Abu Dhabi

Neural Coding of Vibration Intensity

Data. Copyright 2021 Wanjoo Park, New York University Abu Dhabi

Alpha interbrain synchrony during mediated interpersonal touch.

Interpersonal touch plays a crucial role in human communication, development, and wellness. Mediated interpersonal touch (MIT), a technology to distance or virtually simulated interpersonal touch, has received significant attention to counteract the negative consequences of touch deprivation. Studies investigating the effectiveness of MIT have primarily focused on self-reporting or behavioral correlates. It is largely unknown how MIT affects neural processes such as interbrain functional connectivity during human interactions. Given how users exchange haptic information simultaneously during interpersonal touch, interbrain functional connectivity provides a more ecologically valid way of studying the neural correlates associated with MIT. In this study, a palm squeeze task is designed to examine interbrain synchrony associated with MIT using EEG-based hyperscanning methodology. The phase locking value (PLV) index is used to measure interbrain synchrony. Results demonstrate that MIT elicits a significant increase in alpha interbrain synchronization between participants' brains. Especially, there was a significant difference in the alpha PLV indices between no MIT and MIT conditions in the early stage (130-470 ms) of the interaction period (t-test, p < 0.05). Given the role that alpha interbrain synchrony plays during social interaction, a significant increase in PLV index during MIT interaction seems to indicate an effect of social coordination. The findings and limitations of this study are further discussed, and perspectives on future research are provided

Neural Coding of Vibration Intensity

Vibrotactile feedback technology has become widely used in human-computer interaction due to its low cost, wearability, and expressiveness. Although neuroimaging studies have investigated neural processes associated with different types of vibrotactile feedback, encoding vibration intensity in the brain remains largely unknown. The aim of this study is to investigate neural processes associated with vibration intensity using electroencephalography. Twenty-nine healthy participants (aged 18-40 years, nine females) experienced vibrotactile feedback at the distal phalanx of the left index finger with three vibration intensity conditions: no vibration, low-intensity vibration (1.56 g), and high-intensity vibration (2.26 g). The alpha and beta band event-related desynchronization (ERD) as well as P2 and P3 event-related potential components for each of the three vibration intensity conditions are obtained. Results demonstrate that the ERD in the alpha band in the contralateral somatosensory and motor cortex areas is significantly associated with the vibration intensity. The average power spectral density (PSD) of the peak period of the ERD (400-600 ms) is significantly stronger for the high- and low-vibration intensity conditions compared to the no vibration condition. Furthermore, the average PSD of the ERD rebound (700-2,000 ms) is significantly maintained for the high-vibration intensity compared to low-intensity and no vibration conditions. Beta ERD signals the presence of vibration. These findings inform the development of quantitative measurements for vibration intensities based on neural signals

EEG patterns of subacute stroke patients performing motor tasks correlate with motor functional outcome: preliminary results

If an early predictor of motor functional outcome after stroke were available, stroke patients would receive more appropriate treatments for motor recovery. We performed a correlation analysis of the electroencephalography (EEG) signal patterns of nine subacute stroke patients (recorded 22.9 ?? 7.1 days after onset) and their motor recovery rates (measured 100.2 ?? 8.9 days after onset). The beta band spectral power in the bilateral motor cortex after physical upper limb movement correlated significantly with the motor recovery rates [Fugl-Meyer assessment (FMA) scores; Pearson&apos;s linear correlation, p &lt;; 0.05]. The R-squared of a regression model of the FMA scores and the EEG features was 0.89. These results suggest that the EEG patterns in motor areas correlate with motor recovery after stroke and can be used as an early predictor of motor functional outcome

EEG correlates of user satisfaction of haptic sensation

We investigated a correlation between electroencephalography (EEG) power and user satisfaction about haptic sensation. EEG power in alpha, delta, and high beta band showed a significant correlation with haptic satisfaction, especially in the early period. Our results show the feasibility of a novel metric for UI design of consumer electronics

Multi-Task Heterogeneous Ensemble Learning-Based Cross-Subject EEG Classification Under Stroke Patients

Robot-assisted motor training is applied for neurorehabilitation in stroke patients, using motor imagery (MI) as a representative paradigm of brain-computer interfaces to offer real-life assistance to individuals facing movement challenges. However, the effectiveness of training with MI may vary depending on the location of the stroke lesion, which should be considered. This paper introduces a multi-task electroencephalogram-based heterogeneous ensemble learning (MEEG-HEL) specifically designed for cross-subject training. In the proposed framework, common spatial patterns were used for feature extraction, and the features according to stroke lesions are shared and selected through sequential forward floating selection. The heterogeneous ensembles were used as classifiers. Nine patients with chronic ischemic stroke participated, engaging in MI and motor execution (ME) paradigms involving finger tapping. The classification criteria for the multi-task were established in two ways, taking into account the characteristics of stroke patients. In the cross-subject session, the first involved a direction recognition task for two-handed classification, achieving a performance of 0.7419 (&#x00B1;0.0811) in MI and 0.7061 (&#x00B1;0.1270) in ME. The second task focused on motor assessment for lesion location, resulting in a performance of 0.7457 (&#x00B1;0.1317) in MI and 0.6791 (&#x00B1;0.1253) in ME. Comparing the specific-subject session, except for ME on the motor assessment task, performance on both tasks was significantly higher than the cross-subject session. Furthermore, classification performance was similar to or statistically higher in cross-subject sessions compared to baseline models. The proposed MEEG-HEL holds promise in improving the practicality of neurorehabilitation in clinical settings and facilitating the detection of lesions