Patient condition display

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system

Reexamination Certificate

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C600S301000

Reexamination Certificate

active

07031857

ABSTRACT:
Data from a plurality of sensors representing a patient's condition, including measurement signals and also secondary parameters derived from the measurement signals, are displayed in a simple way by calculating a novelty index constituting a one-dimensional visualization space. The novelty index is based on the distance of the current data point in a multi-dimensional measurement space, whose coordinates are defined by the values of the measurement signals and secondary parameters, from a predefined normal point. This may be achieved by using a suitably trained artificial neural network to sum the distance between the current data point in the measurement space and a plurality of prototype points representing normality.

REFERENCES:
patent: 5339826 (1994-08-01), Schmidt et al.
patent: 5419332 (1995-05-01), Sabbah et al.
patent: 5584291 (1996-12-01), Vapola et al.
patent: 5749367 (1998-05-01), Gamlyn et al.
patent: 5800360 (1998-09-01), Kisner et al.
patent: 6063028 (2000-05-01), Luciano
patent: 6134537 (2000-10-01), Pao et al.
patent: 6347310 (2002-02-01), Passera
patent: 6443889 (2002-09-01), Groth et al.
patent: 6571227 (2003-05-01), Agrafiotis et al.
patent: 6647341 (2003-11-01), Golub et al.
patent: 6650779 (2003-11-01), Vachtesvanos et al.
patent: 2 258 311 (1993-02-01), None
patent: 99/65386 (1999-12-01), None
N D Khambete et al., Movement artefact rejection in impedance pneumography using six strategically placed electrodes, Jul. 16, 1999, 2000 IOp Publishing Ltd, pp. 79-88.
Tarassenko et al, “Medical Signal Processing Using the Software Monitor”, DERA/IEE Workshop Intelligent Sensor Processing, Birmingham, UK, Feb. 14, 2001; XP001189057.
Maglaveras et al; “ECG Pattern Recognition and Classification Using Non-Linear Transformations and Neural Networks: A Review”; International Journal of Medicinal Informatics, Elsevier Scientific Publishers, Shannon, IR, vol. 52, No. 1-3, Oct. 1, 1998, pp. 191-208, XP004153684.
Presedo et al; “Cycles of ECG Parameter Evolution During Ischemic Episodes”; Computers In Cardiology, Indianapolis, USA Sep 8-11, 1996, New York, NY, USA, Sep. 8, 1996, pp. 489-492, XP010205943.
Lowe, et al; “Neuroscale: Novel Topographic Feature Extraction With Radial Basis Function Networks”; Advances in Neural Information Processing System 9, Online, 1997, pp. 543-549, XP002219480.
Emdin et al; “Compact Representation of Autonomic Stimulation on Cardiorespiratory Signals by Principal Component Analysis”; Proceedings of the Computers In cardiology Conference, London, Sep. 5-8, 1993, Los Alamitos, IEEE Comp. Soc. Press, US, Sep. 5, 1993, pp. 157-160, XP100128860.
Schwenker et al; “Visualization and Analysis of Signal Averaged High Resolution Electrocardiograms Employing Cluster Anaylsis and MultiDimensional Scaling”; Computers In Cardiology, 1996 Indianapolis, IN, USA Sep. 8-11, 1996, New York, NY, USA, IEEE, US, Sep. 8, 1996, pp. 453-456, XP010205934.
Sammon; “A Nonlinear Mappling for DAT Structure Analysis”; IEEE Transactions on computer, vol. C-18, No. 5, May 1969, pp. 401409.
Tipping et al; “Shadow Targets: A Novel Algorithm for Topographic Projections by Radial Basis Functions”; Artificial Neural Networks, Jul. 7-9, 1997, Conference Publication No. 440, IEEE, 1997, pp. 7-12.
Zahlmann et al; “A Neuro-Fuzzy-Classifier for a Knowledge-Based Glaucoma Monitor”; http://www-ophtel.gsf.de/˜zahlmann/aime97/htm.
Maglaveras et al., “Smart Alarming Scheme for ICU Using Neural Networks”; Computers in Cardiology 1998 IEEE; vol. 25, pp 493-496.
K-Means Clustering Algorithm; http://cne.gmu.edu/modules/dau/stat/clustgalgs/clust513bdy.html ; May 2001.
Abstract—Advances in Patient Connected Monitoring; pp 1-16, Mar. 2001; XP-002219479.
Fernandez E. et al. “Detection of Abnormality in the Electrocardiogram Without Prior Knowledge by Using the Quantisation Error of a Self-Organaising Map, Testing on the European Ischaemia Database”,Medical and Biological Engineering and Computing, Peter Peregrinus, Stevenage, GB, vol. 39, No. 3, May 2001 (2004-2005), pp. 330-337, (XP001178745).
Roberts S.J. “Extreme Values Statistics for Novelty Detection in Biomedical Data Processing”,IEEE Proceedings: Stevenage, Herts, GB, vol. 147, No. 6, Nov. 3, 2000 (200-11-3), pp. 363-367 (XP006014529).

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