Human Activity Monitor - Essay Example

Human Activity Monitor Summary Human activities are the most important actions undertaken in the world. This is because they have a direct impact on the economy hence leading there is need to monitor. In these report analysis of different monitoring methods of human activities is being undertaken. The paper looks into details on the different aspects that should be considered in undertaking monitoring of human activities. Different human activities are undertaken to benefit ones’ self. This makes it important to take a close consideration of how human activities are carried out and how they are taken in the different stage. The report considers all these aspects and explains the reasons as to why such events occur. Table of Contents Summary 1 Introduction 3 Methodology 4 Algorithm 4 Procedure 5 Results 6 Matlab code 7 Conclusion 9 Introduction In the day to day life situation human beings are always carrying out different activities. They carry out this activity with the aim of benefiting themselves and also self-satisfaction. However, the act of monitoring this activity is somehow difficult though scientists have developed different methods of ensuring human activities are monitored. Some of the methods used are the accelerometers. They have been used to ensure that human performance is improved and ensure in every action undertaken the expected results are got in return. Different experiments have been carried out to ensure that improvements are made in ensuring that everything is moving towards the right way. It is due to the following it the reason that the following experiment was carried out to ensure that inner understanding is gained regarding the whole issue. Methodology In undertaking the experiment, it was best that the best method to ensure that the topic is well understood to be used. To ensure that the human activities were understood, running patterns, walking patterns and standing patterns had to be monitored. The three activities were important as they are the daily activities that are being carried out by a normal human being. The three will certainly indicate to what extent that human beings carry out different activities in ensuring the success of their desires. The experiment was undertaken in a manner that those activities that do not count much on the contribution of human beings daily gains were not considered. All the activities that have been monitored depending on what an individual is undertaking were carefully recorded and used in making a conclusion regarding the experiment results. In undertaking the experiment, it was carried out to ensure that all the observation mad throughout accommodate all the vibration and concrete conclusions about them undertaken. Graphs and other statistical methods were used to record the data and analyzing it hence ensuring that everything is involved and nothing is eliminated in the process. The observations that were made were done in a manner to ensure that every activity is brought on board and nothing that was left out. Everything was conducive to ensure that accurate results are recorded in the process without failure. Practical and accurate data was the major source of conclusions that were made in the process. Algorithm A smart mobile phone app known as an accelerometer application was used in collecting the data of a personal activity. A collection of sets of data that are produced in the x, y and z-axis is the way that the application works. Simply by placing the smartphone on the hip, a set of data will be created because of the activity the person is doing whether standing, walking and running. Afterward, the data created by the accelerometer is then imported into Matlab. These data are then analyzed using a specially developed Matlab code. Different variations are created from the different activities that are driven out of the different set of data. Those sets of data will be broken down into small segments to be able to analyze each signal magnitude, therefore using the moving root mean square (RMS) to compute the moving signals. The moving rout means square is a way of computing each individual signal alone over time. Then, after calculating the average moving rms, the stairs graph was plotted. Afterward, analyzing the graph was required in order to pick out the values of thresholds. Moreover, separating each activity signals was required to know the time taken by each activity, and then the time for each activity was represented in percentage in a pie chart by dividing the 100% percentage for all of the activates done. This statistical method was undertaken to ensure that everything was well presented in an accurate manner. Procedure The experiment was undertaken using the smartphone device that was used to measure the vibrations. The app was designed by Diffraction Limited Design LLC with the aim of measuring vibrations. The device was placed vertically in a back pocket of the experimenter to get an accurate reading of vibrations. The recording process of human motion was conducted in one minute only. In this one min, we had to record four readings first standing then shuffle then walking finally running and then walking afterward standing. The final step is extracting the data from the vibration app and use them in MATLAB. The experiment was undertaken accurately to ensure that everything is according to the planned procedures. Conclusions were lastly deducted telling us the whole importance that the experiment contained. Two figures were taken from MATLAB, Pie chart and Stairs graph. Results Figure 1 vibration graph Figure (1) shows the vibration of the human motion. As shown in first 8 seconds and between 28 and 34 seconds the position forms with standing. However, the small vibration shown as walking form and vibrations started raising significantly when the experimenter started running. Figure 2 Pie chart From figure 2 above, the pie chart has been designed to represent the percentage proportionality of human activity in terms of running, walking, and standing, it is observed that correspondents took more time on walking than running and standing still. Running and Standing still which both make 25% and 23% do not beat walking time. As a result, the order in which humans engage in their movement indicates more walking followed with standing time than running. It is one of the best statistics methods that was used to present this data. Matlab code data_aa=uigetfile('*.*'); data=importdata(data_aa); t=data(:,1); y=data(:,4); plot(t,y); xlabel('Time [s]'); ylabel('Acceleration [g]'); si=mean(diff(t)); sr=1/si; w=0.5; wn=floor(sr*w); n=floor(length(y)/wn); sp=1; for i=1:n; ep=sp+wn-1;, yrms(i)=rms(y(sp:ep)); sp=ep+1;; end trms=(0:length(yrms)-1)*w; hold on stairs(trms, yrms,'black', 'LineWidth',1) hold off tsw=0.1; twr=0.7; tstand = 0; twalk = 0; trun = 0; for i=1:length(yrms) if yrms(i)tsw && yrms(i)= twr trun = trun + 1; end end tot=tstand+twalk+trun; stand=100*tstand/tot; walk=100*twalk/tot; run=100*trun/tot; figure(2) x = [stand walk run]; h = pie(x); hText = findobj(h,'Type','text'); % text object handles percentValues = get(hText,'String'); % percent values txt = {'Stand: ';'Walk: ';'Run: '}; % strings combinedtxt = strcat(txt,percentValues); % strings and percent values oldExtents_cell = get(hText,'Extent'); % cell array oldExtents = cell2mat(oldExtents_cell); % numeric array hText(1).String = combinedtxt(1); hText(2).String = combinedtxt(2); hText(3).String = combinedtxt(3); newExtents_cell = get(hText,'Extent'); % cell array newExtents = cell2mat(newExtents_cell); % numeric array width_change = newExtents(:,3)-oldExtents(:,3); signValues = sign(oldExtents(:,1)); offset = signValues.*(width_change/2); textPositions_cell = get(hText,{'Position'}); % cell array textPositions = cell2mat(textPositions_cell); % numeric array textPositions(:,1) = textPositions(:,1) + offset; % add offset hText(1).Position = textPositions(1,:); hText(2).Position = textPositions(2,:); hText(3).Position = textPositions(3,:); Conclusion Some of the best devices that have been invented are accelerometers that can be used to measure human activities. The use of accelerometers in the community has become more noticeable over the years. Accelerometers are used in a range of applications to help improve and analyze the performance of machinery. Accelerometers can also be used to measure the position, orientation, and velocity of a moving object, without the need of another measuring device. These exercise watches help us to monitor our body movements and stay in shape. These watches operate so that, the user is able to analyze a range of bodily movements, like the number of steps, calories, fat, how far they’ve moved, and their heart rate. Throughout the human activity project, we have been given a chance to improve our engineering knowledge of programming and problem solving, by creating a code that can detect in percentage the time a person was doing an activity whether it was standing, walking, or running with the presence of a collected set of signals data. The project was interesting in all of the stages from brainstorming to finalizing and analyzing the results. Both of the graphs plotted showed different results we were seeking, the stairs graph clearly displayed acceleration of the body due to time, while the pie chart showed the time taken by each activity in percentage from the total time recorded. In addition, knowing that acceleration equals the force divided by the mass, we can say that our code would only be successful with a person of similar mass to us. Our code can be improved by calculating greater thresholds for all different type of masses and forces which are important for calculating the acceleration of a body. Read More