Database Needle EMG: MUAP Time Domain Features Download We are making the EMG Time Domain Feature Database available to the research community free of charge. If you use this database in your research, we kindly ask that you reference our papers listed below: • C.S. Pattichis, C.N. Schizas, L. Middleton, Neural Network Models in EMG Diagnosis, IEEE Transactions on Biomedical Engineering, Vol. 42, No. 5, pp. 486-496, 1995. Further download information for the database may be obtained by contacting C. Pattichi (pattichi@ucy.ac.cy). Pre-prints of the papers are also available upon request, or can be downlaoded for personal use from the website of the Laboratory of eHealth of the University of Cyprus, at: http://www.medinfo.cs.ucy.ac.cy/ Database Description For each subject 20 MUAPS were collected. The mean and standard deviation values of the time domain features for 20 MUAPS are given for each subject. Each line represents the features of one subject. Number of features: 7 (given in Columns 1-14 (for mean and standard deviation)) Column 1: Duration Mean in ms Column 2: Duration Standard Deviation in ms Column 3: Amplitude Mean in mV Column 4: Amplitude Standard Deviation in mV Column 5: Spike duration Mean in ms Column 6: Spike duration Standard Deviation in ms Column 7: Spike area Mean in mVms Column 8: Spike area Standard Deviation in mVms Column 9: Number of Phases Mean - no units Column 10: Number of Phases Standard Deviation - no units Column 11: Number of Turns Mean - no units Column 12: Number of Turns Standard Deviation - no units Column 13: Area Mean in mVms Column 14: Area Standard Deviation in mVms Column 15: class; 1=NOR=NORMAL; 2=MND=MOTOR NEURON DISEASE; 3=MYO=MYOPATHY Column 16: Subject or patient number DurMn DurSD AmpMn AmpSD SpDMn SpDSD SpAMn SpASD PhMn PhSD TurMn TurSD ArMn ArSD Cls Pat. No. 8.93 2.77 0.33 0.23 6.05 2.70 0.24 0.17 2.50 0.61 3.10 1.21 0.47 0.38 1 059 10.48 2.83 0.43 0.18 4.39 1.74 0.22 0.10 3.15 0.88 3.60 1.05 0.40 0.22 1 064 11.60 3.40 0.51 0.30 4.77 2.62 0.25 0.13 2.60 0.50 3.00 0.56 0.30 0.19 1 065 9.11 3.01 0.33 0.19 4.78 2.23 0.20 0.12 2.75 0.97 2.95 0.83 0.29 0.23 1 066 9.01 2.04 0.33 0.15 4.86 1.98 0.19 0.07 2.45 0.51 2.75 0.72 0.30 0.21 1 067 10.32 2.14 0.39 0.17 5.93 2.87 0.26 0.14 2.95 1.00 3.35 1.27 0.35 0.19 1 122 8.26 2.12 0.26 0.11 5.43 2.61 0.19 0.08 2.40 0.50 3.00 1.08 0.37 0.27 1 093 9.45 1.74 0.37 0.15 5.63 1.85 0.26 0.09 2.30 0.47 2.75 1.07 0.33 0.22 1 094 9.45 2.86 0.36 0.21 6.08 2.41 0.25 0.13 2.20 0.41 2.55 0.60 0.39 0.55 1 080 10.90 2.37 0.41 0.15 6.82 2.59 0.26 0.09 2.50 0.76 2.75 1.33 0.43 0.29 1 095 8.56 3.06 0.34 0.21 4.97 1.63 0.22 0.12 2.55 0.94 3.65 1.27 0.37 0.34 1 098 9.05 2.72 0.40 0.18 5.31 2.97 0.27 0.12 2.80 1.01 3.30 1.26 0.51 0.36 1 099 15.94 2.37 0.98 0.36 12.98 5.73 0.84 0.40 5.65 2.50 6.20 2.50 0.82 0.34 2 021 14.42 3.17 1.13 1.19 7.81 2.65 0.72 0.56 3.75 1.12 5.75 2.79 0.91 0.73 2 023 14.78 3.42 1.08 0.49 6.29 2.02 0.62 0.27 3.70 1.63 4.75 2.36 0.72 0.43 2 041 14.05 3.69 0.66 0.29 5.48 5.14 0.32 0.27 3.95 1.64 4.00 1.62 0.41 0.19 2 074 12.76 4.65 0.71 0.32 5.86 1.92 0.43 0.19 2.70 0.57 3.05 0.89 0.56 0.30 2 088 13.65 4.00 1.22 0.86 5.82 2.38 0.70 0.51 3.60 1.19 4.05 1.43 0.72 0.50 2 075 11.84 3.74 0.62 0.29 4.32 2.84 0.33 0.16 3.05 0.60 3.60 1.05 0.44 0.17 2 106 11.73 3.92 0.75 0.57 6.53 3.36 0.48 0.37 4.50 2.84 5.95 3.75 0.67 0.55 2 090 14.75 4.52 0.73 0.32 7.63 4.32 0.42 0.22 4.70 1.59 5.55 2.61 0.37 0.13 2 107 10.34 2.39 0.52 0.27 5.15 1.97 0.34 0.18 3.30 1.17 3.60 1.05 0.39 0.18 2 108 13.39 3.12 0.75 0.39 7.58 3.88 0.53 0.28 4.75 2.15 5.75 2.81 0.74 0.37 2 116 8.18 1.52 0.25 0.09 4.36 2.19 0.15 0.08 2.70 1.03 3.10 1.37 0.28 0.19 3 022 8.65 3.08 0.40 0.29 3.52 1.32 0.23 0.17 2.75 0.72 2.95 1.00 0.34 0.24 3 068 5.41 1.34 0.16 0.08 2.97 1.31 0.10 0.05 2.50 0.95 3.25 1.37 0.33 0.24 3 069 6.87 2.19 0.20 0.14 4.10 1.57 0.13 0.09 2.40 0.75 3.05 1.15 0.24 0.14 3 082 4.91 0.98 0.12 0.11 3.45 0.79 0.08 0.07 2.25 0.55 2.40 0.75 0.29 0.24 3 060 6.99 2.15 0.18 0.10 4.62 1.48 0.12 0.06 3.05 1.15 3.65 1.57 0.25 0.20 3 091 7.89 2.60 0.18 0.10 6.12 2.55 0.15 0.09 2.75 0.97 2.80 0.95 0.21 0.09 3 104 6.37 1.76 0.18 0.13 4.57 1.80 0.14 0.12 2.70 0.92 3.05 1.10 0.26 0.20 3 111 9.74 2.15 0.48 0.31 4.92 1.77 0.32 0.21 3.25 1.07 3.70 1.38 0.40 0.33 3 096 7.07 1.62 0.30 0.12 4.83 1.16 0.22 0.10 2.60 0.94 3.45 1.36 0.44 0.27 3 061 6.57 1.22 0.23 0.16 2.90 1.07 0.15 0.15 3.10 1.33 3.10 1.17 0.43 0.40 3 114 Copyright Notice -----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------ Copyright (c) 2010 University of Cyprus, Cyprus All rights reserved. Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this database and its documentation for any purpose, provided that the copyright notice in its entirety appear in all copies of this database, and the original source of this database, the Laboratory of eHealth at the University of Cyprus (http://www.medinfo.cs.ucy.ac.cy/) is acknowledged in any publication that reports research using this database. The following papers are to be cited in the bibliography whenever the database is used as: • C.S. Pattichis, C.N. Schizas, L. Middleton, Neural Network Models in EMG Diagnosis, IEEE Transactions on Biomedical Engineering, Vol. 42, No. 5, pp. 486-496, 1995. 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