Unobtrusive Sensing of Psychophysiological Parameters

The quantification of the human perception of experiences can be achieved by the sensing of specific psychophysiological parameters. A growing interest develops for the daily life use of these quantification techniques by unobtrusive and unnoticeable data collection. Remote and non invasive sensing technologies are discussed for the sensing of the following psychophysiological parameters: heart rate variability, and muscle stress. A generic miniature platform for miniature wireless sensing applications is described as an important enabler for unobtrusive and unnoticeable sensing. The technology no longer seems to be a limiting factor for unobtrusive and unnoticeable sensing. Initially the sensors will be worn on the body, but ultimately implantable sensors will become widely accepted, allowing access to new parameters, such as hormone levels and body core temperature.

[1]  Geert Langereis,et al.  Contactless EMG sensors embroidered onto textile , 2007, BSN.

[2]  Kay Römer,et al.  The design space of wireless sensor networks , 2004, IEEE Wireless Communications.

[3]  Oliver Chiu-sing Choy,et al.  Preparing smartcard for the future: from passive to active , 2004, IEEE Transactions on Consumer Electronics.

[4]  Jan Beutel Metrics for Sensor Network Platforms , 2006 .

[5]  T. Armstrong,et al.  A conceptual model for work-related neck and upper-limb musculoskeletal disorders. , 1993, Scandinavian journal of work, environment & health.

[6]  Mike Horton,et al.  The platforms enabling wireless sensor networks , 2004, CACM.

[7]  Jose L. Van Velzen,et al.  Cortical and autonomic correlates of visual selective attention in introverted and extraverted children , 2005 .

[8]  M.R. Neuman,et al.  Insulated Active Electrodes , 1970, IEEE Transactions on Industrial Electronics and Control Instrumentation.

[9]  John G. Webster,et al.  Medical Instrumentation: Application and Design , 1997 .

[10]  R H Westgaard,et al.  Generation of muscle tension additional to postural muscle load. , 1987, Ergonomics.

[11]  Louise Venables,et al.  The influence of task demand and learning on the psychophysiological response. , 2005, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[12]  Paul Lukowicz,et al.  A systematic approach to the design of distributed wearable systems , 2004, IEEE Transactions on Computers.

[13]  D. Modi IEC 601-1-2 and its impact on medical device manufacturers , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[14]  C J Harland,et al.  High resolution ambulatory electrocardiographic monitoring using wrist mounted electric potential sensors , 2003 .

[15]  Ko Keun Kim,et al.  Common Mode Noise Cancellation for Electrically Non-Contact ECG Measurement System on a Chair , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[16]  Andreas Neudeck,et al.  Textile-Based Electronic Substrate Technology , 2004 .

[17]  Mark Weiser The computer for the 21st century , 1991 .