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It has been suggested that effectively detecting the stress level of a computer user could possibly develop the computers' ability to respond intelligently and help the user relax from negative emotional states during human-computer interaction. Our research focuses on the use of three physiological signals: Blood Volume Pulse (BVP), Galvanic Skin Response (GSR) and Pupil Diameter (PD), to automatically monitor the stress state of computer users. This paper reports on the hardware and software instrumentation development and signal processing approach used to detect changes in the stress level of a subject interacting with a computer, within the framework of a specific experimental task. For this experiment a computer game was implemented on the basis of a clinical mental stress test, called the 'Stroop Test', adapted to make the subject experience two different levels of stress, while his/her BVP, GSR and PD signals were continuously recorded. Several data processing techniques were applied to extract effective attributes of the 'stress' state of the subjects. Current results indicate that there exists a strong correlation among changes in those three signals and the shift in the emotional states when stress stimuli are applied to the interaction environment.
Stress Tracker-Detecting Acute Stress From a Trackpad: Controlled Study
Background: Stress is a risk factor associated with physiological and mental health problems. Unobtrusive, continuous stress sensing would enable precision health monitoring and proactive interventions, but current sensing methods are often inconvenient, expensive, or suffer from limited adherence. Prior work has shown the possibility to detect acute stress using biomechanical models derived from passive logging of computer input devices. Objective: Our objective is to detect acute stress from passive movement measurements of everyday interactions on a laptop trackpad: (1) click, (2) steer, and (3) drag and drop. Methods: We built upon previous work, detecting acute stress through the biomechanical analyses of canonical computer mouse interactions and extended it to study similar interactions with the trackpad. A total of 18 participants carried out 40 trials each of three different types of movement-(1) click, (2) steer, and (3) drag and drop-under both relaxed and stressed conditions. Results: The mean and SD of the contact area under the finger were higher when clicking trials were performed under stressed versus relaxed conditions (mean area: P=.009, effect size=0.76; SD area: P=.01, effect size=0.69). Further, our results show that as little as 4 clicks on a trackpad can be used to detect binary levels of acute stress (ie, whether it is present or not). Conclusions: We present evidence that scalable, inexpensive, and unobtrusive stress sensing can be done via repurposing passive monitoring of computer trackpad usage.
Use of force plate instrumentation to assess kinetic variables during touch screen use
Universal Access in The Information Society
Touch screens are becoming ubiquitous technology, allowing for enhanced speed and convenience of user interfaces. To date, the majority of touch screen usability studies have focused on timing and accuracy of young, healthy individuals. This information alone may not be sufficient to improve accessibility and usability of touch screens. Kinetic data (e.g. force, impulse, and direction) may provide valuable information regarding human performance during touch screen use. Since kinetic information cannot be measured with a touch screen alone, touch screen-force plate instrumentation, software, and methodology were developed. Individuals with motor control disabilities (Cerebral Palsy and Multiple Sclerosis), as well as gender- and age-matched non-disabled participants, completed a pilot reciprocal tapping task to evaluate the validity of this new instrumentation to quantify touch characteristics. Results indicate that the instrumentation was able to successfully evaluate performance and kinetic characteristics. The kinetic information measured by the new instrumentation provides important insight into touch characteristics which may lead to improved usability and accessibility of touch screens.
A method of measuring fingertip loading during keyboard use
Journal of Biomechanics, 1994
A single keycap on a standard alphanumeric computer keyboard was instrumented with a piezoelectric load cell and the fingertip motion was recorded with a high-speed video motion analysis system. Contact force histories between the fingertip and the keycap were recorded while four subjects typed a standard text for five minutes. Each keystroke force history is characterized by three distinct phases: (I) keyswitch compression, (II) finger impact and (III) fingertip pulp compression and release. Each keystroke force history contained two relative maxima, one in phase II and one in phase III. The subject mean peak forces ranged from 1.6 to 5.3 N and the subject mean peak fingertip velocities ranged from 0.3 to 0.7 m/s. Motion analyses and force measurements suggest a ballistic model of finger motion during typing.
Much progress has been made during the last 40 years in the quest to improve the interaction of humans with computers. While new modalities of communication between computers and their users continue to be found and enhanced (e.g., speech recognition for human-to-computer communication and speech synthesis for computer-to-human communication), the nature of the exchange between computers and users remains, for the most part, dry and mechanistic. The emerging field of Affective Computing seeks to advance Human-Computer Interaction (HCI) by enabling computers to interact with users in ways appropriate to their affective states. However, a major prerequisite to the fulfillment of the promise of Affective Computing is the development of efficient mechanisms for Affective Sensing, i.e., the ability of the computer to assess the affective state of its user, particularly when it shifts to uncomfortable states, such as stress. Our research pursues the use of three physiological signals: Blood Volume Pulse (BVP), Galvanic Skin Response (GSR) and Pupil Diameter (PD), to automatically monitor the level of stress in computer users. This paper reports on the hardware and software instrumentation development and signal processing approach used to detect the stress level of a subject interacting with a computer, within the framework of a specific experimental task, which is called the 'Stroop Test'. The Stroop Effect is evoked by the mismatch between the font color and the meaning of a certain word (name of a color), displayed to the experimental subject. For this experiment, a computer game was implemented and adapted to make the subject experience this effect, while his/her BVP, GSR and PD signals were continuously recorded. Three data processing techniques were applied to extract effective attributes of the stress level of the subjects throughout the experiment. Current results indicate that there exists a correspondence between changes in those three signals and the shift in the emotional states when stress stimuli are applied to the interaction environment.