Biocybernetic Adaptation Research Articles

Fatigue-aware videogame using biocybernetic adaptation: a pilot study for upper-limb rehabilitation with sEMG

Fatigue-aware videogame using biocybernetic adaptation: a pilot study for upper-limb rehabilitation with sEMG

A Psychophysiological Model of Firearms Training in Police Officers: A Virtual Reality Experiment for Biocybernetic Adaptation.

Crucial elements for police firearms training include mastering very specific psychophysiological responses associated with controlled breathing while shooting. Under high-stress situations, the shooter is affected by responses of the sympathetic nervous system that can impact respiration. This research focuses on how frontal oscillatory brainwaves and cardiovascular responses of trained police officers (N = 10) are affected during a virtual reality (VR) firearms training routine. We present data from an experimental study wherein shooters were interacting in a VR-based training simulator designed to elicit psychophysiological changes under easy, moderate and frustrating difficulties. Outcome measures in this experiment include electroencephalographic and heart rate variability (HRV) parameters, as well as performance metrics from the VR simulator. Results revealed that specific frontal areas of the brain elicited different responses during resting states when compared with active shooting in the VR simulator. Moreover, sympathetic signatures were found in the HRV parameters (both time and frequency) reflecting similar differences. Based on the experimental findings, we propose a psychophysiological model to aid the design of a biocybernetic adaptation layer that creates real-time modulations in simulation difficulty based on targeted physiological responses.

Enhancing Virtual Rehabilitation in Upper Limbs With Biocybernetic Adaptation: The Effects of Virtual Reality on Perceived Muscle Fatigue, Game Performance and User Experience

Virtual rehabilitation has been used during decades to provide a more personalized, controlled, and enjoyable experience on upper-limb motor rehabilitation. Since novel virtual reality (VR) technologies are now accessible and highly immersive, the challenge for a wide dissemination of virtual rehabilitation in clinical scenarios has shifted from the hardware robustness to the software intelligence. A sophisticated technique that provides physiological intelligence to novel human-computer interaction (HCI) applications is biocybernetic adaptation. The concept emerges from the electrophysiological computing field, and it proposes using body signals to detect human states (e.g. workload or fatigue) and modulate the virtual activity accordingly. This paper evaluates the effects of using biocybernetic adaptation in a virtual rehabilitation game that aims to encourage users to exert at a desirable intensity level while interacting with the virtual environment. The system relies on surface-electromyography (sEMG) signals to detect fatigue levels in real-time and adapt the game challenge dynamically. Perceived fatigue levels, game user experience, and game performance parameters are assessed after playing the game, considering two different visualization modalities: non-immersive (conventional flat screen) and immersive (VR headset). Results revealed how the biocybernetic system in the immersive condition not only produced lower levels of perceived fatigue compared with the non-immersive, but also, created a more enjoyable and positive experience in a controlled experiment with 24 healthy subjects. Moreover, participants in the immersive condition showed a better performance in the virtual game and higher usability levels scored by users compared with the non-immersive condition. To conclude, we highlight the importance of combining novel immersive approaches with physiologically aware systems to enhance the benefits of virtual rehabilitation therapies.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop.

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed.

Biocybernetic adaptation and privacy

Biocybernetic adaptation is a new approach to optimizing human–computer interfaces and human–computer interaction. Bio-signals and, more broadly, vital data of a person are collected and interpreted in real time by a computer in order to trigger its own adaptive processes. The collection of highly sensitive data is thus a necessary condition for the purpose of making the application more user-friendly. Therefore, the most obvious and important social, legal and ethical issues in this kind of application are privacy and data protection. In this research note we report from a technology assessment project for the European Parliament. We provide some conceptual distinctions, highlight the most promising application fields, and discuss privacy challenges and potential regulatory actions to be taken.

Capturing user engagement via psychophysiology: measures and mechanisms for biocybernetic adaptation

The concept of task engagement is associated with effortful striving to reach a desired goal. This dimension is fundamental for software designed to elicit high quality performance. This paper will review the concept of task engagement, both in the psychological literature and with respect to affective computing approaches, such as biofeedback and the definition of ‘flow’ states. This paper will briefly describe a series of laboratory experiments designed to explore measures of task engagement based on EEG and cardiovascular measures. These experiments employed a number of manipulations to influence task engagement, e.g. performance feedback, task difficulty and financial incentives. Results demonstrated the sensitivity of EEG measures to cognitive sources of engagement (e.g. mental workload) whilst cardiovascular variables tended to respond to the motivation to achieve. We use these findings to explore how real-time monitoring of engagement may generate adaptive dynamics for software design using a computer game as an exemplar system.

Establishing the Psychophysiological Variables that can Identify & Predict Operator Subjective State

Biocybernetic adaptation describes a system wherein automation is regulated by the operator's physiology. The identification of real-time psychophysiological variables capable of detecting and predicting operator subjective states is an important requisite for biocybernetic control. The present study investigated how psychophysiology may index negative subjective states, namely, task-disengagement, distress and worry. To encourage negative states, 35 participants performed the (high demand) Multi-Attribute Task Battery (MATB), for 100 minutes in total. Subjective state was assessed using the Dundee Stress State Questionnaire (DSSQ). The psychophysiological measures recorded included: GSR, EOG, EEG, ECG, and respiration. Analysis of the data revealed performance was sustained throughout the task although subjective states became more negative over time. This was accompanied by various psychophysiological changes, e.g. increased respiration rate. Regression analyses indicated that psychophysiological changes were predictive of changes in subjective states. The results and implications for biocybernetic systems are discussed.