Galvanic Skin Response

14,000,000 Leading Edge Experts on the ideXlab platform

Scan Science and Technology

Contact Leading Edge Experts & Companies

Scan Science and Technology

Contact Leading Edge Experts & Companies

The Experts below are selected from a list of 246 Experts worldwide ranked by ideXlab platform

Fang Chen - One of the best experts on this subject based on the ideXlab platform.

  • Galvanic Skin Response-Based Measures
    Robust Multimodal Cognitive Load Measurement, 2016
    Co-Authors: Fang Chen, Jianlong Zhou, Yang Wang, Syed Z. Arshad, Ahmad Khawaji, Dan Conway
    Abstract:

    This chapter focuses on the use of Galvanic Skin Response (GSR) for cognitive load measurement. GSR is a measure of conductivity of human Skin, and provides an indication of changes within the human sympathetic nervous system.

  • using Galvanic Skin Response for cognitive load measurement in arithmetic and reading tasks
    Australasian Computer-Human Interaction Conference, 2012
    Co-Authors: Nargess Nourbakhsh, Fang Chen, Yang Wang, Rafael A Calvo
    Abstract:

    Galvanic Skin Response (GSR) has recently attracted researchers' attention as a prospective physiological indicator of cognitive load and emotions. However, it has commonly been investigated through single or few measures and in one experimental scenario. In this research, aiming to perform a comprehensive study, we have assessed GSR data captured from two different experiments, one including text reading tasks and the other using arithmetic tasks, each imposing multiple cognitive load levels. We have examined temporal and spectral features of GSR against different task difficulty levels. ANOVA test was applied for the statistical evaluation. Obtained results show the strong significance of the explored features, especially the spectral ones, in cognitive workload measurement in the two studied experiments.

  • Galvanic Skin Response gsr as an index of cognitive load
    Human Factors in Computing Systems, 2007
    Co-Authors: Yu Shi, Natalie Ruiz, Ronnie Taib, Eric H C Choi, Fang Chen
    Abstract:

    Multimodal user interfaces (MMUI) allow users to control computers using speech and gesture, and have the potential to minimise users. experienced cognitive load, especially when performing complex tasks. In this paper, we describe our attempt to use a physiological measure, namely Galvanic Skin Response (GSR), to objectively evaluate users. stress and arousal levels while using unimodal and multimodal versions of the same interface. Preliminary results show that users. GSR readings significantly increase when task cognitive load level increases. Moreover, users. GSR readings are found to be lower when using a multimodal interface, instead of a unimodal interface. Cross-examination of GSR data with multimodal data annotation showed promising results in explaining the peaks in the GSR data, which are found to correlate with sub-task user events. This interesting result verifies that GSR can be used to serve as an objective indicator of user cognitive load level in real time, with a very fine granularity.

Thad Starner - One of the best experts on this subject based on the ideXlab platform.

Geetha Shivakumar - One of the best experts on this subject based on the ideXlab platform.

  • Galvanic Skin Response: A Physiological Sensor System for Affective Computing
    International Journal of Machine Learning and Computing, 2013
    Co-Authors: P A Vijaya, Geetha Shivakumar
    Abstract:

    —Electro-dermal Response of any bio-medical system is the change in electrical properties of Skin due to variation in physiological and psychological conditions. The change is caused by the degree to which a person's sweat glands are active. Psychological status of a person tends to make the glands active and this change the Skin resistance. Drier the Skin is, higher will be the Skin resistance. This variation in Skin resistance ranges from 5kΩ to 25kΩ. In the current work, a subject whose Galvanic Skin Response (GSR) is to be measured, has been shown/played a movie clipping, images or recorded audio signals. Depending upon the theme, emotion will be evoked in the subject. Due to the change in emotion, GSR varies. This variation in GSR is recorded for a fixed time interval. In the present work, a total of 75 subjects are selected. People from different age groups and social background, both male and female have been carefully considered. Data acquisition and analysis is carried out by using LabVIEW. The results obtained are convincing and follows the ground reality with a high level of accuracy. As the subject also gives the feedback about the emotions he/she experienced, the results obtained are validated.

Jae Yong Song - One of the best experts on this subject based on the ideXlab platform.

  • flexible Galvanic Skin Response sensor based on vertically aligned silver nanowires
    Sensors and Actuators B-chemical, 2018
    Co-Authors: Sun Hwa Park, Jihye Park, Han Nah Park, Hyunmin Park, Jae Yong Song
    Abstract:

    Abstract Skin conductance is an important bio-signal and generally measured between two fingers using a commercial Galvanic Skin Response (GSR) sensor. In this study, an ultra-thin (6 μm thick) and highly flexible GSR (f-GSR) sensor was developed for application to wearable devices. The f- GSR sensor consists of a Ag-Au core-shell nanowire array embedded in polyimide matrix. Since the nanowire array is vertically aligned in the matrix, the f-GSR sensor has anisotropic electrical conductivity, i.e., electrically conducting in the thickness-direction and electrically insulating in the in-plane direction. Results show that after the nanowire tips contacted Skin they did not degrade during repeated measurement for three months, indicating the mechanical and chemical stability of the f-GSR sensor. The f-GSR sensor exhibits significantly better sensitivity than a commercial sensor: the f-GSR sensor can detect an NaCl solution mimicking human sweat in the concentration range of 10−6 to 1 M. The f-GSR sensor is expected to be used in wearable or patch healthcare devices.

Tracy Westeyn - One of the best experts on this subject based on the ideXlab platform.