This is a lecture focused on pelvic floor dysfunction in elite male sport especially football. It addressed the assessment and management of Pelvic pain in elite sport. Gerard Greene is a men's health physio who works in Birmingham UK ( Birmingham Men's Health Physio Clinic ) and Southampton UK ( Dr Ruth Jones ) .
This is a lecture focused on pelvic floor dysfunction in elite male sport especially football. It addressed the assessment and management of Pelvic pain in elite sport. Gerard Greene is a men's health physio who works in Birmingham UK ( Birmingham Men's Health Physio Clinic ) and Southampton UK ( Dr Ruth Jones ) .
Consider a 4-Link robot manipulator shown below. Use the forward kine.pdfmeerobertsonheyde608
Consider a 4-Link robot manipulator shown below. Use the forward kinematic D-H table and
write an m file that plots the manipulator. The instructions are given in the module 6. Submit
your solutions by the due date, in a single MATLAB m file.
Solution
Please give the kinetic D-H table else it would be difficult to code as we need to know the
rotation spin axis and other momentum of manipulator
Stating a general example code for manipulator with data
function X = fwd_kin(q,x)
% given a position in the configuration space, calculate the position of
% the end effector in the workspace for a two-link manipulator.
% q: vector of joint positions
% x: design vector (link lengths)
% X: end effector position in cartesian coordinates
% configuration space coordinates:
q1 = q(1); % theta 1
q2 = q(2); % theta 2
% manipulator parameters:
l1 = x(1); % link 1 length
l2 = x(2); % link 2 length
% calculate end effector position:
X = [l1*cos(q1) + l2*cos(q1+q2)
l1*sin(q1) + l2*sin(q1+q2)];
% SimulateTwolink.m uses inverse dynamics to simulate the torque
% trajectories required for a two-link planar robotic manipulator to follow
% a prescribed trajectory. It also computes total energy consumption. This
% code is provided as supplementary material for the paper:
%
% \'Engineering System Co-Design with Limited Plant Redesign\'
% Presented at the 8th AIAA Multidisciplinary Design Optimization
% Specialist Conference, April 2012.
%
% The paper is available from:
%
% http://systemdesign.illinois.edu/publications/All12a.pdf
%
% Here both the physical system design and control system design are
% considered simultaneously. Manipulator link length and trajectory
% specification can be specified, and torque trajectory and energy
% consumption are computed based on this input. It was found that maximum
% torque and total energy consumption calculated using inverse dynamics
% agreed closely with results calculated using feedback linearization, so
% to simplify optimization problem solution an inverse dynamics approach
% was used, which reduces the control design vector to just the trajectory
% design.
%
% In the conference paper several cases are considered, each with its own
% manipulator task, manipulator design, and trajectory design. The
% specifications for each of these five cases are provided here, and can be
% explored by changing the case number variable (cn).
%
% This code was incorporated into a larger optimization project. The code
% presented here includes only the analysis portion of the code, no
% optimization.
%
% A video illustrating the motion of each of these five cases is available
% on YouTube:
%
% http://www.youtube.com/watch?v=OR7Y9-n5SjA
%
% Author: James T. Allison, Assistant Professor, University of Illinois at
% Urbana-Champaign
% Date: 4/10/12
clear;clc
% simulation parameters:
p.dt = 0.0005; % simulation step size
tf = 2; p.tf = tf; % final time
p.ploton = 0; % turn off additional plotting capabilities
p.ploton2 = 0;
p.Tallow = 210; % maximum .
I need help understanding the Pan Tompkins algorythm, and Id also .pdfeyewatchsystems
I need help understanding the Pan Tompkins algorythm, and I\'d also like to know how to detect
QRS peaks of the ECG (with circles, for example). I\'m using the script in this website as a
guidance, but I have trouble understanding what it\'s doing. Perhaps there\'s a simpler way to do
it? http://cnx.org/contents/YR1BUs9_@1/QRS-Detection-Using-Pan-Tompki
Our teacher has otherwise explained to us FIR filters, and wants us to use them instead of the
low pass, high pass that are mentioned in the website and though I do understand how they work,
I don\'t really know which window is the best, or how many coefficients the filter needs. I\'ve
applying the cut-off frequencies 5-15 because I\'ve seen that\'s where the QRS peaks are
concentrated. Is there any way to improve this as well?
TB=1;
TBn=TB/Fs;
N2=ceil(3.3/TBn);
Fc1 =5;
Fc2 =15 ;
wc1 = 2*pi*Fc1;
wc2 = 2*pi*Fc2;
wcn1 = 2*pi*Fc1/Fs;
wcn2 = 2*pi*Fc2/Fs;
Bz=fir1(N2,[wcn1 wcn2]);
y3=filter(Bz,1,x1);
figure; plot(x1); figure; plot(y3);
Solution
Save the function and use it as given below ::
pan_tompkin(ECG1,200,1) 1st is ECG raw data , 2nd is sampling frequency, 3rd is
for plots -always set it to 1
Matlab Code ------------------------------------ function .
function [qrs_amp_raw,qrs_i_raw,delay]=pan_tompkin(ecg,fs,gr)
%% function [qrs_amp_raw,qrs_i_raw,delay]=pan_tompkin(ecg,fs)
% Complete implementation of Pan-Tompkins algorithm
%% Inputs
% ecg : raw ecg vector signal 1d signal
% fs : sampling frequency e.g. 200Hz, 400Hz and etc
% gr : flag to plot or not plot (set it 1 to have a plot or set it zero not
% to see any plots
%% Outputs
% qrs_amp_raw : amplitude of R waves amplitudes
% qrs_i_raw : index of R waves
% delay : number of samples which the signal is delayed due to the
% filtering
if ~isvector(ecg)
error(\'ecg must be a row or column vector\');
end
if nargin < 3
gr = 1; % on default the function always plots
end
ecg = ecg(:); % vectorize
%% Initialize
qrs_c =[]; %amplitude of R
qrs_i =[]; %index
SIG_LEV = 0;
nois_c =[];
nois_i =[];
delay = 0;
skip = 0; % becomes one when a T wave is detected
not_nois = 0; % it is not noise when not_nois = 1
selected_RR =[]; % Selected RR intervals
m_selected_RR = 0;
mean_RR = 0;
qrs_i_raw =[];
qrs_amp_raw=[];
ser_back = 0;
test_m = 0;
SIGL_buf = [];
NOISL_buf = [];
THRS_buf = [];
SIGL_buf1 = [];
NOISL_buf1 = [];
THRS_buf1 = [];
%% Plot differently based on filtering settings
if gr
if fs == 200
figure, ax(1)=subplot(321);plot(ecg);axis tight;title(\'Raw ECG Signal\');
else
figure, ax(1)=subplot(3,2,[1 2]);plot(ecg);axis tight;title(\'Raw ECG Signal\');
end
end
%% Noise cancelation(Filtering) % Filters (Filter in between 5-15 Hz)
if fs == 200
%% Low Pass Filter H(z) = ((1 - z^(-6))^2)/(1 - z^(-1))^2
b = [1 0 0 0 0 0 -2 0 0 0 0 0 1];
a = [1 -2 1];
h_l = filter(b,a,[1 zeros(1,12)]);
ecg_l = conv (ecg ,h_l);
ecg_l = ecg_l/ max( abs(ecg_l));
delay = 6; %based on the paper
if gr
ax(2)=subplot(322);plot(ecg_l);axis tight;title(\'Low pass filtered\');
end
%% High Pas.
System Software/Operating Sytems lab reportVishnu K N
This is my lab report for the System Software Lab ,APJ Abdul Kalam Kerala Technological University,Kerala-S5 Computer Science.Hope you guys appreciate it.
System Software /Operating System Lab ReportVishnu K N
This is my report of System Software/Operating System lab for APJ Abdul Kalaam Kerala Technological University ,B Tech,S5 Computer Science.Please pardon me if there are any mistakes.
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