scholarly journals A NOVEL SIGNAL PROCESSING METHOD BASED ON FREQUENCY MODALITY FOR INTRA-BODY MEDICAL INSTRUMENT TRACKING

2014 ◽  
pp. 22-29
Author(s):  
Dimitrios A. Fotiadis ◽  
Kostas Papathanasiou ◽  
Alexandros Astaras ◽  
Panagiotis D. Bamidis ◽  
Anestis Kalfas

Measuring the position of a medical instrument inside the human body can be performed with various methods. One option is to measure the phase shift of the signal originating from a transmitter embedded into the tip of the medical instrument, determining its displacement with respect to a set of stationary receivers. The phase shift is converted into a low frequency voltage with the use of a Phased Locked Loop (PLL). This voltage can subsequently be converted into displacement, providing the position of the medical instrument in one (1D), two (2D) and three (3D) dimensions using trilateration. The instrument’s displacement can be defined in either the time or frequency domain. This paper presents a novel method for constant velocity displacement of the transmitter, using either the Locally Weighted Scatter-Plot Smoothing (LOWESS) curve fitting method or a Lomb-Scargle periodogram. The Lomb-Scargle periodogram is based on the least-squares power spectrum and can be used instead of waveform smoothing and measurement into the time domain, providing more precise and accurate measurement results as compared to LOWESS curve fitting method.

2012 ◽  
Vol 19 (2) ◽  
pp. 381-394
Author(s):  
José Pereira ◽  
Octavian Postolache ◽  
Pedro Girão

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System PerformanceThis paper presents a voltammetric segmented voltage sweep mode that can be used to identify and measure heavy metals' concentrations. The proposed sweep mode covers a set of voltage ranges that are centered around the redox potentials of the metals that are under analysis. The heavy metal measurement system can take advantage of the historical database of measurements to identify the metals with higher concentrations in a given geographical area, and perform a segmented sweep around predefined voltage ranges or, alternatively, the system can perform a fast linear voltage sweep to identify the voltammetric current peaks and then perform a segmented voltage sweep around the set of voltages that are associated with the voltammetric current peaks. The paper also includes the presentation of two auto-calibration modes that can be used to improve system's reliability and proposes the usage of a Gaussian curve fitting of voltammetric data to identify heavy metals and to evaluate their concentrations. Several simulation and experimental results, that validate the theoretical expectations, are also presented in the paper.


2010 ◽  
Vol 26 (6-8) ◽  
pp. 801-811 ◽  
Author(s):  
Mingxiao Hu ◽  
Jieqing Feng ◽  
Jianmin Zheng

1993 ◽  
Vol 272 (1) ◽  
pp. 125-134 ◽  
Author(s):  
James M. Jordan ◽  
Michael D. Love ◽  
Harry L. Pardue

2007 ◽  
Vol 46 (13) ◽  
pp. 4549-4560 ◽  
Author(s):  
Q. Peter He ◽  
Jin Wang ◽  
Martin Pottmann ◽  
S. Joe Qin

Author(s):  
Bhavish Sushiel Agarwal ◽  
Jyoti R Desai ◽  
Snehanshu Saha

The use of hand gestures opens a wide range of application for human computer interaction. The paper makes use of haar classifiers and camShift algorithm to track the movement of hand. Parallelism is introduced at every step by segmenting the data from camshaft into an NxN grid. Every block of the grid now represents a lead point which is calculated from mean of all the points belonging to the particular grid. Now we have only N2 points to recognize the curve that was performed by the user in his action. Finally the fit that was found is compared to pre-defined curve fit data to find out the curve using Mahalanobis equation. Parallelism used in reducing the number of points to be fitted allows the recognition to be faster.


2014 ◽  
Vol 35 (11-12) ◽  
pp. 996-1006
Author(s):  
Hou Kuan Tam ◽  
Lap Mou Tam ◽  
Afshin J. Ghajar ◽  
Pak Hang Fu ◽  
Cheong Sun

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