UNOBTRUSIVE SENSING OF PSYCHOPHYSIOLOGICAL PARAMETERS Some Examples of Non-Invasive Sensing Technologies

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 technolo- gies are discussed for the sensing of the following psychophysiological param- eters: 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 sen- sors 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]  T. Armstrong,et al.  A conceptual model for work-related neck and upper-limb musculoskeletal disorders. , 1993, Scandinavian journal of work, environment & health.

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

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

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

[5]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

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

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

[8]  B. P. Bogert,et al.  The quefrency analysis of time series for echoes : cepstrum, pseudo-autocovariance, cross-cepstrum and saphe cracking , 1963 .

[9]  Akif Ündar,et al.  Medical instrumentation: Application and design , 1997 .

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

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

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

[13]  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.

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

[15]  Emile H. L. Aarts,et al.  The New Everyday: Views on Ambient Intelligence , 2003 .

[16]  Kwang Suk Park,et al.  Common mode noise cancellation for electrically non-contact ECG measurement system on a chair. , 2005, Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference.

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

[18]  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).

[19]  Roberto Merletti,et al.  Electromyography. Physiology, engineering and non invasive applications , 2005 .

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

[21]  M. Bryce.  Muscles Alive: Their Functions Revealed by Electromyography , 1963 .

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