iPhys: An Open Non-Contact Imaging-Based Physiological Measurement Toolbox

This study tests whether playing violent video games leads to desensitization and increased cardiovascular responding. In a laboratory experiment, 42 men spent 20 min playing either a high- or low-violence version of a “first-person shooter” game. Arousal (heart rate, respiration rate) was measured continuously. After playing the game, emotional responses to aversive and aggressive stimuli - pictures from Lang, Bradley, and Cuthbert’s (1999) International Affective Picture System - were assessed with self-ratings and physiological measurement (skin conductance). Results showed no differences in the judgments of emotional responses to the stimuli. However, different effects of game violence emerged in the physiological reactions to the different types of stimulus material. Participants in the high-violence condition showed significantly weaker reactions (desensitization) to aversive stimuli and reacted significantly more strongly (sensitization) to aggressive cues. No support was found for the arousal hypothesis. Post-hoc analyses are used to discuss possible moderating influences of gaming experience and player’s trait aggressiveness in terms of the General Aggression Model ( Anderson & Bushman, 2001 ) and the Downward Spiral Model ( Slater, Henry, Swaim, & Anderson, 2003 ).

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Investigation of Objective Assessment Scale for Sound Reproduction System Based on Psychological and Physiological Measurement

The Journal of The Institute of Image Information and Television Engineers ◽

10.3169/itej.61.825 ◽

2007 ◽

Vol 61 (6) ◽

pp. 825-827 ◽

Cited By ~ 1

Author(s):

Tomoharu Ishikawa ◽

Akio Nozawa ◽

Minoru Mitsui ◽

Touta Mizuno ◽

Hideto Ide ◽

...

Keyword(s):

Objective Assessment ◽

Assessment Scale ◽

Physiological Measurement ◽

Sound Reproduction ◽

Reproduction System

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Health informatics. Testing of physiological measurement software

10.3403/30035878 ◽

2008 ◽

Keyword(s):

Health Informatics ◽

Physiological Measurement ◽

Measurement Software

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Non-invasive cuff-less blood pressure estimation using a hybrid deep learning model

Optical and Quantum Electronics ◽

10.1007/s11082-020-02667-0 ◽

2021 ◽

Vol 53 (2) ◽

Author(s):

Sen Yang ◽

Yaping Zhang ◽

Siu-Yeung Cho ◽

Ricardo Correia ◽

Stephen P. Morgan

Keyword(s):

Machine Learning ◽

Blood Pressure ◽

Deep Learning ◽

Absolute Error ◽

Learning Model ◽

Physiological Measurement ◽

British Hypertension Society ◽

Non Invasive ◽

Blood Pressure Estimation ◽

Deep Learning Model

AbstractConventional blood pressure (BP) measurement methods have different drawbacks such as being invasive, cuff-based or requiring manual operations. There is significant interest in the development of non-invasive, cuff-less and continual BP measurement based on physiological measurement. However, in these methods, extracting features from signals is challenging in the presence of noise or signal distortion. When using machine learning, errors in feature extraction result in errors in BP estimation, therefore, this study explores the use of raw signals as a direct input to a deep learning model. To enable comparison with the traditional machine learning models which use features from the photoplethysmogram and electrocardiogram, a hybrid deep learning model that utilises both raw signals and physical characteristics (age, height, weight and gender) is developed. This hybrid model performs best in terms of both diastolic BP (DBP) and systolic BP (SBP) with the mean absolute error being 3.23 ± 4.75 mmHg and 4.43 ± 6.09 mmHg respectively. DBP and SBP meet the Grade A and Grade B performance requirements of the British Hypertension Society respectively.

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Characterizing the Effects of Explosive Ordnance Disposal Operations on the Human Body While Wearing Heavy Personal Protective Equipment

Human Factors The Journal of the Human Factors and Ergonomics Society ◽

10.1177/0018720821992623 ◽

2021 ◽

pp. 001872082199262

Author(s):

Yi-Ning Wu ◽

Adam Norton ◽

Michael R. Zielinski ◽

Pei-Chun Kao ◽

Andrew Stanwicks ◽

...

Keyword(s):

Human Body ◽

Personal Protective Equipment ◽

Evaluation Methodology ◽

Protective Equipment ◽

Physiological Measurement ◽

Cognitive Stress ◽

Explosive Ordnance Disposal ◽

And Performance ◽

Inspection Tasks ◽

Muscle Activations

Objective To provide a comprehensive characterization of explosive ordnance disposal (EOD) personal protective equipment (PPE) by evaluating its effects on the human body, specifically the poses, tasks, and conditions under which EOD operations are performed. Background EOD PPE is designed to protect technicians from a blast. The required features of protection make EOD PPE heavy, bulky, poorly ventilated, and difficult to maneuver in. It is not clear how the EOD PPE wearer physiologically adapts to maintain physical and cognitive performance during EOD operations. Method Fourteen participants performed EOD operations including mobility and inspection tasks with and without EOD PPE. Physiological measurement and kinematic data recording were used to record human physiological responses and performance. Results All physiological measures were significantly higher during the mobility and the inspection tasks when EOD PPE was worn. Participants spent significantly more time to complete the mobility tasks, whereas mixed results were found in the inspection tasks. Higher back muscle activations were seen in participants who performed object manipulation while wearing EOD PPE. Conclusion EOD operations while wearing EOD PPE pose significant physical stress on the human body. The wearer’s mobility is impacted by EOD PPE, resulting in decreased speed and higher muscle activations. Application The testing and evaluation methodology in this study can be used to benchmark future EOD PPE designs. Identifying hazards posed by EOD PPE lays the groundwork for developing mitigation plans, such as exoskeletons, to reduce physical and cognitive stress caused by EOD PPE on the wearers without compromising their operational performance.

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