Affective computing vs. affective placebo: Study of a biofeedback-controlled game for relaxation training

Relaxation training is an application of affective computing with important implications for health and wellness. After detecting user׳s affective state through physiological sensors, a relaxation training application can provide the user with explicit feedback about his/her detected affective state. This process (biofeedback) can enable an individual to learn over time how to change his/her physiological activity for the purposes of improving health and performance. In this paper, we provide three contributions to the field of affective computing for health and wellness. First, we propose a novel application for relaxation training that combines ideas from affective computing and games. The game detects user׳s level of stress and uses it to influence the affective state and the behavior of a 3D virtual character as a form of embodied feedback. Second, we compare two algorithms for stress detection which follow two different approaches in the affective computing literature: a more practical and less costly approach that uses a single physiological sensor (skin conductance), and a potentially more accurate approach that uses four sensors (skin conductance, heart rate, muscle activity of corrugator supercilii and zygomaticus major). Third, as the central motivation of our research, we aim to improve the traditional methodology employed for comparisons in affective computing studies. To do so, we add to the study a placebo condition in which user׳s stress level, unbeknown to him/her, is determined pseudo-randomly instead of taking into account his/her physiological sensor readings. The obtained results show that only the feedback presented by the single-sensor algorithm was perceived as significantly more accurate than the placebo. If the placebo condition was not included in the study, the effectiveness of the two algorithms would have instead appeared similar. This outcome highlights the importance of using more thorough methodologies in future affective computing studies.     

The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications

The investigation of innovative Human-Computer Interfaces (HCI) provides a challenge for future multimedia research and development. Brain-Computer Interfaces (BCI) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as Amyotrophic Lateral Sclerosis (ALS) or spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity game, could define a new level of control possibilities also for healthy customers decoding information directly from the user’s brain, as reflected in electroencephalographic (EEG) signals which are recorded non-invasively from user’s scalp. This contribution introduces the Berlin Brain–Computer Interface (BBCI) and presents setups where the user is provided with intuitive control strategies in plausible gaming applications that use biofeedback. Yet at its beginning, BBCI thus adds a new dimension in multimedia research by offering the user an additional and independent communication channel based on brain activity only. First successful experiments already yielded inspiring proofs-of-concept. A diversity of multimedia application models, say computer games, and their specific intuitive control strategies, as well as various Virtual Reality (VR) scenarios are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates.

Mobile cloud-based physical activity advisory system using biofeedback sensors

Physical inactivity has gained a wide attention due to its negative influence on human wellness. Physical activity advisory systems consider a promising solution for this phenomenon. In this paper, we propose a mobile cloud-based physical activity advisory system utilizing biofeedback sensors and environmental context data based on calories expenditure from performing various activities by tracking user’s physical movements. To evaluate the proposed system, we conducted in total a three-month experiment on six users. For each user, we tracked the amount of burnt calories from the physical movements for a two-week period. During the first week, the system did not send any advice, while during the second week, the system was advising the user on activities to perform. The compared results of the two weeks collected data (without and with advice) reflect the positive effect of the proposed system on participants’ physical activity level. The system motivates them to reach or exceed the recommended number of calories to be burned daily.     

Interactively mediating experiences of mindfulness meditation

Sonic Cradle is a human–computer interaction paradigm designed to foster meditative attentional patterns. A user׳s body is suspended comfortably in a completely dark sound chamber while the interaction paradigm subtly encourages them to focus on their breathing to summon and progressively shape an abstract immersive sound experience. Basic interpretive qualitative methods with a purposive sample of 39 participants were used to systematically analyze interview data after a 15-min experience of the system. Results suggest that this persuasive medium can pleasantly encourage an experience comparable to mindfulness by consistently inducing a calm mental clarity and loss of intention. Surprisingly, participants also reported perceptual illusions, feelings of floating, and emotional responses. Mounting evidence implies mindfulness meditation as an effective practice for self-regulation; this study represents a first step toward realizing technology׳s potential to increase wellbeing by introducing people to this psychologically beneficial contemplative practice.     

美国景观视觉资源规划设计方法评析及新技术改进潜力分析

尽管环境视觉感知领域有深厚科研积累,但由于系统性理论及实证缺乏、感受信息采集失真、缺乏实景信息互动等问题,景观视觉规划设计实践仍然相对薄弱。本文以美国景观视觉资源管理方法为研究对象,采用历史研究和预实验的方法,以选取美国林务局视觉规划为例,总结了传统景观视觉规划设计中可能存在的主要问题,并在此基础上介绍了如何通过包括生物反馈信息采集、地理信息协同平台、增强现实等技术对目前景观视觉规划设计过程进行优化和模拟检验。预实验结果表明上述若干新技术对于改进现有视觉规划设计方法有一定的效果,并分析了新技术的发展潜力。     

Neurofeedback Treatment of College Students' Test on Anxiety, Depression, Personality, and Mood

Biofeedback is used to treat the mental diseases of college students, such as test anxiety, depression, personality, and mood. Anxiety of the colleague students was first tested by test anxiety scale （TAS） and then treated by biofeedback. After getting the biofeedback treatment, the students＇ TAS scores, blood volume pulse, and skin conductance were decreased, especially, their TAS scores dropped markedly. Meanwhile, the level of EEG （61 rhythm/a rhythm） and peripheral temperature increased observably. Then, neurofeedbaek （β1 rhythm/α rhythm） was applied to treat students＇ depression, personality, and mood. As a result, these three kinds of symptoms got alleviated. And their therapeutic effects based on neurofeedback were more stable, durative and less reerudescent.     

Controller design for human-robot interaction

Many robotics tasks require a robot to share the same workspace with humans. In such settings, it is important that the robot performs in such a way that does not cause distress to humans in the workspace. In this paper, we address the problem of designing robot controllers which minimize the stress caused by the robot while performing a given task. We present a novel, data-driven algorithm which computes human-friendly trajectories. The algorithm utilizes biofeedback measurements and combines a set of geometric controllers to achieve human friendliness. We evaluate the comfort level of the human using a Galvanic Skin Response (GSR) sensor. We present results from a human tracking task, in which the robot is required to stay within a specified distance without causing high stress values.

基于生物反馈技术的便携式心电监测系统的设计

基于生物反馈技术,引入生物反馈训练,设计了一种具有放松疗法、行为疗法功能,并可实现无线数据传输的便携式心电监测系统。应用MATLAB软件,给出了在MATLAB环境中分析心电监测数据的原理和方法,简单实现了心电数据的家庭化分析。由此可更好地调动患者的主观能动作用,使其自发地进行心理、生理活动的内在调节,从而达到预防疾病或治疗疾病的目的。     

Adaptation in Observers During Television Quality-Grading Tests I. Adaptation as a Function of the Conditioning Situation

The results of subjective quality-grading tests aro affected by ‘ adaptation ’ in the sense that observers become more critical when the quality of the tost material is generally high, and vice versa- The phenomenon has been investigated for tests with television pictures impaired by random noise and by a long-delayed echo. The magnitude of the effect of adaptation as a function of the ‘ conditioning situation ’ is described in terms of ‘ adaptation coefficients ’; it is greater for random noise.