Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of... more Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with electroencephalography (EEG) is increasingly popular owing to its mobility and its ability to allow studying social interactions in naturalistic settings at the millisecond scale. Approach. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposes a clock-synchronized method that uses a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional radio frequency channels to keep the counter of their receiving dongles updated, which guarantees that binding event markers received by the dongle with the EEG time series have the correct timestamp. Main results. The results of two simulation experiments and one video gaming experiment reveal that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase lag and negligible amplitude difference between the signals. Significance. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.
Journal of Medical and Biological Engineering, 2010
An EEG-based smart living environmental control system to auto-adjust the living environment is p... more An EEG-based smart living environmental control system to auto-adjust the living environment is proposed in this study. Many environmental control systems have been proposed to improve human life quality in recent years. However, there is little research focused on environment control by using a human's physiological state directly. Even though some studies have proposed brain computer interface-based (BCI-based) environmental control systems, most of them encountered signal quality decline during long-term physiological monitoring with conventional wet electrodes. Moreover, such BCI-based environmental control systems are actively controlled by users; less close-loop feedback capability can be provided between environment and user for automation. Based on the advance of our technique for BCI and the improvement of micro-electro-mechanical-system-based (MEMS-based) dry electrode sensors, we combined these techniques to demonstrate an auto-adjustable living environment control sy...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, Jan 18, 2016
Potable electroencephalography (EEG) devices have become critical for important research. They ha... more Potable electroencephalography (EEG) devices have become critical for important research. They have various applications, such as in brain computer interfaces (BCI). Numerous recent investigations have focused on the development of dry sensors, but few concern the simultaneous attachment of high-density dry sensors to different regions of the scalp to receive qualified EEG signals from hairy sites. An inflatable and wearable wireless 32-channel EEG device was designed, prototyped, and experimentally validated for making EEG signal measurements; it incorporates spring-loaded dry sensors and a novel gasbag design to solve the problem of interference by hair. The cap is ventilated and incorporates a circuit board and battery with a high-tolerance wireless (Bluetooth) protocol and low power consumption characteristics. The proposed system provides a 500/250 Hz sampling rate, and 24 bit EEG data to meet the BCI system data requirement. Experimental results prove that the proposed EEG sys...
Handbook of Digital Games and Entertainment Technologies, 2015
Abstract : Brain-computer interface (BCI) technologies, or technologies that use online brain sig... more Abstract : Brain-computer interface (BCI) technologies, or technologies that use online brain signal processing, have a great promise to improve human interactions with computers, their environment, and even other humans. Despite this promise, there are no current serious BCI technologies in widespread use, due to the lack of robustness in BCI technologies. The key neural aspect of this lack of robustness is human variability, which has two main components: (1) individual differences in neural signals and (2) intraindividual variability over time. In order to develop widespread BCI technologies, it will be necessary to address this lack of robustness. However, it is currently unknown how neural variability affects BCI performance. To accomplish these goals, it is essential to obtain data from large numbers of individuals using BCI technologies over considerable lengths of time. One promising method for this is through the use of BCI technologies embedded into games with a purpose (GWAP). GWAP are a game-based form of crowdsourcing which players choose to play for enjoyment and during which the player performs key tasks which cannot be automated but that are required to solve research questions. By embedding BCI paradigms in GWAP and recording neural and behavioral data, it should be possible to much more clearly understand the differences in neural signals between individuals and across different time scales, enabling the development of novel and increasingly robust adaptive BCI algorithms.
The 13th International Conference on Solid-State Sensors, Actuators and Microsystems, 2005. Digest of Technical Papers. TRANSDUCERS '05.
Abstract A novel method has been developed for the manufacture of a three dimensional multi-elect... more Abstract A novel method has been developed for the manufacture of a three dimensional multi-electrode array (3D MEA), particularly, the shape of micro-tips can be varied by MEMS technology to construct different multi-electrode array. It improved the disadvantage of ...
Online artifact rejection, feature extraction, and pattern recognition are essential to advance t... more Online artifact rejection, feature extraction, and pattern recognition are essential to advance the Brain Computer Interface (BCI) technology so as to be practical for real-world applications. The goals of BCI system should be a small size, rugged, lightweight, and ...
Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of... more Objective. Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with electroencephalography (EEG) is increasingly popular owing to its mobility and its ability to allow studying social interactions in naturalistic settings at the millisecond scale. Approach. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposes a clock-synchronized method that uses a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional radio frequency channels to keep the counter of their receiving dongles updated, which guarantees that binding event markers received by the dongle with the EEG time series have the correct timestamp. Main results. The results of two simulation experiments and one video gaming experiment reveal that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase lag and negligible amplitude difference between the signals. Significance. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.
Journal of Medical and Biological Engineering, 2010
An EEG-based smart living environmental control system to auto-adjust the living environment is p... more An EEG-based smart living environmental control system to auto-adjust the living environment is proposed in this study. Many environmental control systems have been proposed to improve human life quality in recent years. However, there is little research focused on environment control by using a human's physiological state directly. Even though some studies have proposed brain computer interface-based (BCI-based) environmental control systems, most of them encountered signal quality decline during long-term physiological monitoring with conventional wet electrodes. Moreover, such BCI-based environmental control systems are actively controlled by users; less close-loop feedback capability can be provided between environment and user for automation. Based on the advance of our technique for BCI and the improvement of micro-electro-mechanical-system-based (MEMS-based) dry electrode sensors, we combined these techniques to demonstrate an auto-adjustable living environment control sy...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, Jan 18, 2016
Potable electroencephalography (EEG) devices have become critical for important research. They ha... more Potable electroencephalography (EEG) devices have become critical for important research. They have various applications, such as in brain computer interfaces (BCI). Numerous recent investigations have focused on the development of dry sensors, but few concern the simultaneous attachment of high-density dry sensors to different regions of the scalp to receive qualified EEG signals from hairy sites. An inflatable and wearable wireless 32-channel EEG device was designed, prototyped, and experimentally validated for making EEG signal measurements; it incorporates spring-loaded dry sensors and a novel gasbag design to solve the problem of interference by hair. The cap is ventilated and incorporates a circuit board and battery with a high-tolerance wireless (Bluetooth) protocol and low power consumption characteristics. The proposed system provides a 500/250 Hz sampling rate, and 24 bit EEG data to meet the BCI system data requirement. Experimental results prove that the proposed EEG sys...
Handbook of Digital Games and Entertainment Technologies, 2015
Abstract : Brain-computer interface (BCI) technologies, or technologies that use online brain sig... more Abstract : Brain-computer interface (BCI) technologies, or technologies that use online brain signal processing, have a great promise to improve human interactions with computers, their environment, and even other humans. Despite this promise, there are no current serious BCI technologies in widespread use, due to the lack of robustness in BCI technologies. The key neural aspect of this lack of robustness is human variability, which has two main components: (1) individual differences in neural signals and (2) intraindividual variability over time. In order to develop widespread BCI technologies, it will be necessary to address this lack of robustness. However, it is currently unknown how neural variability affects BCI performance. To accomplish these goals, it is essential to obtain data from large numbers of individuals using BCI technologies over considerable lengths of time. One promising method for this is through the use of BCI technologies embedded into games with a purpose (GWAP). GWAP are a game-based form of crowdsourcing which players choose to play for enjoyment and during which the player performs key tasks which cannot be automated but that are required to solve research questions. By embedding BCI paradigms in GWAP and recording neural and behavioral data, it should be possible to much more clearly understand the differences in neural signals between individuals and across different time scales, enabling the development of novel and increasingly robust adaptive BCI algorithms.
The 13th International Conference on Solid-State Sensors, Actuators and Microsystems, 2005. Digest of Technical Papers. TRANSDUCERS '05.
Abstract A novel method has been developed for the manufacture of a three dimensional multi-elect... more Abstract A novel method has been developed for the manufacture of a three dimensional multi-electrode array (3D MEA), particularly, the shape of micro-tips can be varied by MEMS technology to construct different multi-electrode array. It improved the disadvantage of ...
Online artifact rejection, feature extraction, and pattern recognition are essential to advance t... more Online artifact rejection, feature extraction, and pattern recognition are essential to advance the Brain Computer Interface (BCI) technology so as to be practical for real-world applications. The goals of BCI system should be a small size, rugged, lightweight, and ...
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