final report project #35 3d electromagnetic field mapping

of 23

Aalto University, School of Electrical Engineering

Automation and Electrical Engineering (AEE) Master's Programme

ELEC-E8002 & ELEC-E8003 Project work course

Year 2017

Final Report

Project #35

3D Electromagnetic Field Mapping Device (EMF Map)

Date: 29.5.2017

Faisal Usman

Sami Ollila

Klaus Hamara

Saijariina Kuokkanen

of 23

Information page Students

Faisal Usman

Sami Ollila

Klaus Hamara

Saijariina Kuokkanen

Project manager

Faisal Usman

Official Instructor

Ilkka Laakso

Other advisors

Starting date

5.1.2017

Completion date

29.5.2017

Approval

The Instructor has accepted the final version of this document

Date: 28.5.2017

of 23

Abstract

Magnetic field measurements are frequently conducted in several industrial applications. There are

various methods for measuring magnetic field including inductive and Hall-sensor methods.

However, these methods are usually used to measure magnetic field in a single point. The

measuring instrument can be moved but the measurements cannot be precisely and systematically

tied together. Therefore, modeling and calculating a complete three-dimensional magnetic field of

the target object is impossible or at least very challenging.

Despite its challenging nature, 3D measurement of magnetic fields are currently still needed.

Passing of the new EU directive which implies that every employer in European Union must ensure

that their employees are not exposed to dangerously high magnetic fields. However, the

harmfulness of magnetic field is not defined purely on the strength but the three-dimensional

distribution of the field must also be taken into account. Therefore, the current measuring

equipment is not enough to confirm the harmfulness of a magnetic field.

To provide solution to given problem, this project focused on developing a modern 3D magnetic

field mapping device. The first prototype of the device was introduced in [1] and we continued to

improve the design. Measuring device uses magnetic field probe, Kinect camera, gyroscope and

Matlab to measure and map 3D magnetic fields. This project focused on improving the usability,

user interface and overall operation of the system. This included increasing automation of the

measuring process and some changes to hardware and software. Resulting system now provides

simple and quick way to measure and visualize 3D magnetic field structures.

of 23

Table of Contents Abstract ................................................................................................................................................ 3 Table of Contents ................................................................................................................................. 4 1. Introduction .................................................................................................................................. 5 2. Objective ...................................................................................................................................... 5 3. Project plan .................................................................................................................................. 6

4. Hardware System ......................................................................................................................... 7 4.1. Kinect Sensor ........................................................................................................................ 7 4.2. Magnetic Field Probe ............................................................................................................ 8 4.3. PicoScope .............................................................................................................................. 9 4.4. Inertial Measurement Unit..................................................................................................... 9

5. Results ........................................................................................................................................ 10 6. Reflection of the Project ............................................................................................................ 12

6.1. Reaching objective .............................................................................................................. 12

6.2. Timetable ............................................................................................................................. 13 6.3. Risk analysis ........................................................................................................................ 13 6.4. Project Meetings .................................................................................................................. 14

7. Discussion and Conclusions ...................................................................................................... 15

List of Appendixes ............................................................................................................................. 16 8. References .................................................................................................................................. 16 Appendix A. 3D EMF Map User Guide ............................................................................................ 17 Appendix B. 3D Notes of the 3D EMF Map code structure .............................................................. 20

Appendix C. Important codes ............................................................................................................ 20

of 23

1. Introduction

The presence of electromagnetic field everywhere on earth and also throughout the space is being

studied and its impact and applications has been discussed, researched and proved extensively.

There is unanimous agreement around globe on the rapid increase in the strength of magnetic fields

induced by electronics, industry and communication as time goes on. Therefore, its impacts and

applications are now under consideration in different parts of the world and effort are being made to

define the criteria of safety limits for human exposure to magnetic fields and also for EMF related

applications that affect the environment. In view of this, European Union has made some initiatives

and compiled an EU directive in which safety limits for the electric field induced within the human

body by magnetic field have been defined. To calculate electric field induced inside human body,

strength of magnetic field needs to be measured and three dimensionally modeled. In view of this,

there is a need to develop a tool that will measure and model magnetic fields in different

environments.

The topic of this project is related to electromagnetic field (EMF) and the idea was to develop a

real-time 3D magnetic field measurement and visualization system. With the measurement device

and software measurement of magnetic fields and calculation of induced electric fields induced to

nearby human bodies could be conducted.

There is currently no straightforward way to measure the electric currents that magnetic fields

induce in human body. There are mostly just devices to measure magnetic fields on single points or

the measurements are meant for inspecting small devices such as cell phones.

This work is extended version of already implemented project which was designed previously to

measure magnetic field strength and in the same time provide probe orientation and the 3D

distribution of magnetic field. The previous system measured magnetometer position with Kinect

camera and the orientation with IOS App. The used magnetometer is ELT-400 three axis induction

coil sensors from Narda. The system provides knowledge about how far from their sources the

magnetic fields reach [1]. However, the designed prototype has certain limitations in terms of

usability, measurement and data processing.

2. Objective

The objective of our project was to make improvements in the usability and extend the prototype

magnetic field measurement and visualization system. These improvements will include better and

optimized data processing from Kinect sensor, adjust in measuring tools and simplification of the

user interface of the system. This improves measuring capability in different environments with the

completed system. The project final product will be able to record the physical parameters of the

magnetic fields in 3D space and also visualize the results on a PC.

The Users will be able to use it for verifying safe magnetic field strengths of objects and

environments. The goal related to user experience is that using the system should be as effortless as

possible. There will be minimal need for calibration and the system should start and finish with a

press of a button. The expected performance will depend on the data the measurement system

provides about magnetic fields which should be accurate enough so that it can be used to analyze

of 23

the safety of magnetic fields. The product will be a system that users can perform measurements of

wide variety of different objects.

Overall the whole project was mainly comprised of two parts:

Hardware System, which consists of magnetic measurement probe with gyroscope

accompanied with Kinect Sensor. The probe is connected to computer with Picoscope

oscilloscope that process data to the software. Software system developed in MATLAB will receive the measured values from the

measuring devices, generates 3D model, and calculates the electric field induced by worker

at that place.

3. Project plan

Project Work was started from first week of January, to accomplish a smooth and successful

conclusion of the project plan. Project Plan was carefully designed and scheduled in a way that the

project would be completed within the deadline. In order to meet requirements and expected

outcome, Project was divided into six work packages with 10 Milestones. The work resources were

distributed as per availability of each member and project schedule and accumulated worked hours

for each member was 215 excluding Seminar Hours, Business Aspect Seminar, Team Meetings and

Final Gala. For detailed project plan refer to Appendix (C).

Project started well and deadlines were met in almost all the tasks. Some of tasks were removed,

altered and some task schedule were changed to make it more realistic and achievable and

ultimately towards product. Like task#4.3 Design of Oscilloscope, it was removed from the project

plan because there was a risk that some limitations may come with microcontroller while

developing it. The counter measure for the risk was to eliminate this task from the project. Similarly

task #3.4 Addition of the orientation data to the visualization of magnetic fields was adjusted since

this task required availability of probe orientation data. Orientation measuring system was still not

scheduled to be ready for quite some time so the schedule of this task was changed. These changes

were processed through Change Request Document by Head of WP and Professor accepts the

Change Request.

The team was comprised of four members whereas this identified working areas for this project

were Project Management, MATLAB coding, Development of Hardware and Documentation.

Project Management and Documentation was majorly done by project manager Faisal Usman,

MATLAB coding was done by Sami Ollila and Development of Hardware was done by Klaus

Hamara and Saijariina Kuokkanen.

Professor Laakso provided all the required material and arranged for the required equipment for the

hardware. Project Manager was responsible for communication, meeting arrangements, scheduling

and risk management.

Some measures were taken for a successful project and these were achieving milestones within

deadline, quality and correctness of work and reaching the required goal which was set initially in

the project plan. In view of this and analyzing the final outcome, the project is successful.

of 23

4. Hardware System

This chapter describes the measurement tools that were part of measuring real time magnetic field.

The completed hardware module has a magnetic field strength measuring probe, Inertial

Measurement Unit (IMU) for measuring probe orientation, Kinect camera for measuring probe

position and Picoscope oscilloscope to channel the probe data to PC. In addition there were two

Arduino microcontrollers to wirelessly transmit orientation data from the sensor on probe to the PC.

4.1. Kinect Sensor

Kinect Sensor is an RGB camera device which was basically designed for gaming purposes. The

Kinect sensor is Microsoft product. The v2 which is its advanced version is used for this project. It

is equipped with high resolution and good quality depth images as compared to previous model.

This sensor exhibits improved skeleton tracking abilities and less noise level. The technical

specifications of this version are mentioned in Table 4.1

Table 4.1 Technical Specification of Kinect Sensor [1]

Color image resolution 1920 × 1080

Depth and infrared image resolution 512 × 424

Field of view 70 × 60 degrees

Frame Rate 30 Hz

Range 0.5 – 4.5 m

Accuracy in depth measurement 2 mm

Connection type USB 3.0

Sound Array of four microphones

Power 12V, 2.67 A

In this project, Kinect sensor will to attain field distribution around the magnetic field probe. The

Kinect sensor will use its skeleton tracking feature to track the magnetic field probe during the

magnetic field strength measurement. The Kinect sensor is built for the skeleton tracking purpose

and its SDK includes ready-to-use algorithms for skeletal data collection, which makes this method

easier to implement compared to the time consuming and complex ways of image processing [1].

When magnetic field probe is in either left or right, its center tracked as left or right hand joint

which enables acquisition of 3D coordinates of probe in the real time. The probe tracking is

illustrated in figure 4.1.

of 23

Figure 4.1 Tracking of Arm Joint [1]

The Kinect uses 3D Point Cloud technique to generate image of a scene which have color

information and depth values. Point cloud contains 3D coordinates as well as color values in real

world coordinate system.

4.2. Magnetic Field Probe

In this project, the ELT-400 Exposure Level Tester of Narda, a three-axis induction coil sensor, was

used for the measurement of the magnetic fields [1]. The frequency of probe ranges from 1 Hz to

400 kHz. The technical specification of this probe is given in Table 4.2. This project focuses on

measuring the low-frequency fields, below 10 MHz, so the magnetic field -device in question is

suitable for this purpose [1]. The ELT-400 consists of an external isotropic 100 m2 magnetic field

probe, which contains three orthogonal sensor coils, and the actual measurement device [1], which

is shown in figure 4.2.

Table 4.2 Technical Specification Orientation Probe [1]

Figure 4.2 Probe and Magnetic field Tester [1]

The probe contains different modes for measurement of strength of magnetic field which are given

in table 4.3.

of 23

Table 4.3 Level for measurement of magnetic field strength [1]

4.3. PicoScope

he magnetic field strength probe sends its reading by using Picoscope, USB Oscilloscope. In this

project model 2406b was used. It is a four channel picoscope shown in figure 4.3 and its technical

specifications are given in table 4.4. It generally has two data collection modes: streaming mode

and block mode. Block mode uses the scope to collect a block of the samples whereas streaming

mode collects continuous data. Streaming mode is used for this project in order to obtain real time

data collection.

Figure 3 PicoScope [1]

Table 4 Technical Specification of PicoScope [1]

4.4. Inertial Measurement Unit

MPU6050 is used for collecting orientation data of the probe. It contains three axis accelerometers

and three axis gyroscope. Its technical specifications are given in table 4.5. MPU6050 is aligned

with the angle of probe so that accurate positioning can be achieved. The data collected from it and

of 23

measurement probe with sampling frequency of 1Hz – 100 Hz. The data from orientation probe,

Kinect and teslameter use time stamps which enables data synchronization.

Table 4.5 Technical Specification of MPU-6050

Dimensions 25.5 x 15.2 x 2.48mm

Input Voltage 2.3 - 3.4V

I2C Digital-output 6 or 9-axis MotionFusion data in rotation matrix, quaternion, Euler Angle,

or raw data format

Gyroscope Sensitivity up to 131 LSBs/dps and a full-scale range of ±250, ±500,

±1000, and ±2000dps

Accelerometer Programmable full scale range of ±2g, ±4g, ±8g and ±16g

Digital Motion

Processing™

Offloads complex MotionFusion, sensor timing synchronization and

gesture detection

Other Digital-output temperature sensor

Embedded algorithms for run-time bias and compass calibration.

No user intervention required

5. Results

The goal of the project was to simplify the usage of an existing system. The original system was

very impractical to use and was more of a “proof of concept” than actual practical system. We

identified the following parts of the system that would need improvement:

1. Collecting the data from PicoScope (oscilloscope) required the usage of a separate program.

The user also had to ensure to save the data manually to the right folder.

2. Collecting the orientation data from the probe required the usage of an iPhone and running a

separate Python script. Again, the user had to then save this data to the right folder

manually.

3. If the user wanted to visualize the data after the measurement, they had to use poorly

commented and confusingly implemented separate Matlab scripts to do this.

4. The calibration of the gyroscope had to be performed before every measurement because the

zero point of the gyroscope shifts, which causes the calibration values to change between

measurements.

It was clear that to simplify the system we would need to eliminate the need for multiple separate

programs/scripts by handling all their roles in a single Matlab script.

PicoScope data collection is now done by using a Matlab library provided the manufacturer.

The orientation data collection part has been replaced with a wireless Arduino system based on

Bluetooth. Python code was no longer necessary because Matlab can read the orientation data from

the USB serial the receiving Arduino is connected to.

of 23

Now all the collected data is processed, visualized and saved automatically after the measurement if

the user wants it. As the original measurement system, the improved system visualizes

measurements in two ways. Because the magnetic field data contains several frequencies, the

frequency distribution is useful to show in a separate figure. The highest frequency is shown yellow

in a spectrogram that visualizes the frequency over time. The highest frequency is useful to know

because it is the frequency used in 3D image measurements, for example.

The Kinect takes two images, a depth and a color image, to create a 3D point cloud image. The

image visualizes the strength of EMF in colors from blue to red and shows the position of data

points in measurement environment.

See figures 5.1 and 5.2 for examples of the visualizations produced by the updated system.

Figure 5.1 Spectrogram image produced by the updated system.

of 23

Figure 5.2 Point cloud visualization image produced by the updated system.

The new gyroscope doesn’t need to be calibrated before every measurement as it has built in

features that minimize the errors. The gyroscope axis must still be aligned with Kinect and it must

be kept very still in a level position for roughly 11 seconds after turning it on. This is to ensure that

the autocalibration of the gyroscope will work as intended.

In addition, the Matlab code is now divided into clear entities and features are explained in the

code. Now it is easier to extend the code and add features. For more specific information about the

code refer to Appendix at the end of this document.

6. Reflection of the Project

6.1. Reaching objective

The objective of our project was to improve already implemented system in terms of:

Optimized data processing from Kinect sensor

Adjustment in measuring tools

Simplification the user interface of the system

At the end of the course and closure of project, all three main objectives have been achieved. The

road map designed to reach the final goal was found realistic and result oriented one. Now the

improved system has optimized data from Kinect Sensor, Measurement tool is quite automated with

the whole process and whole system is simplified and now it is more user friendly.

of 23

6.2. Timetable

The timetable was initially set for the completion of tasks was majorly remained unchanged.

Whereas some changes were made when found necessary and more realistic approach. Overall, the

schedule for each Work Package was remained as it is and didn’t require any change and Head of

WPs have concluded respective WPs within the deadline.

The break down for the work resource of each member was set according to the related task and its

schedule as well as availability of member. The work resource for each member was variable but

there is an agreement of completing 215 hours by each member during whole course. This value of

hour was obtained after subtracting compulsory hours of course which included hours related to

lectures, Business Aspect Seminar, Team Meetings and Final Gala.

The estimated time for our project was well justified. To complete 10 credits, one should cover 280

hours. As this project was extension of already executed project, so we didn’t need to struggle a lot

for the idea and feasibility analysis and moreover, related data was already available. Although,

every member estimated maximum hours for compilation of the report. But as in terms of technical

details, there was no such thing to be documented as it was already available. Overall time

management was good and there was no severity with the schedule and there were no precedence

and successors in the early part of the project and each WP team has worked and finished all related

tasks within the finish date.

6.3. Risk analysis

There were some risks listed in Project Plan and these are also given in table 6.1. These were

projected while compiling Project Plan.

Table 6.1 Risks along with severity, likelihood and counter measures

Risks Severity Likelihood Counter Measures

Lack of Theory 3 2 Proper and sufficient material will be

provided

MATLAB incompetence 4 3 Lack of MATLAB skills will be improved

with the help of Instructor

Insufficient MATLAB resource

person

3 4 Improvement and documentation of the code

as well as introduction from the responsible

person of the Matlab code at the beginning

of the integration phase

Design Error 4 2 More time has given literature and design

phase to obtain sufficient knowledge

Too Optimistic Schedule 3 2 Sufficient work hours have been allotted and

of 23

in case work hours will not enough then

work hours related to dissemination WP will

be compensated

Unavailability of group member(s) 4 2 Workload have been divided equally and

have everyone involved in every aspect of

the project. In case of unavailability of group

member then affected workload will be

divided among rest of group members and

project plan will suffer changes.

Micro Controller incompatibilities 3 2 Micro Controller will be change

Lack of Communication 5 1 Meeting Schedule and Communication plan

will be ensured.

All the included risks were crucial and therefore countermeasures were quite clear otherwise they

may cause lagged in project schedule and also affect the goal of the project. There was no risk other

than mentioned ones appeared. During the project, some already mentioned risks appeared which

included are mentioned below.

Micro Controller incompatibilities related to design of Oscilloscope

Lack of theory

MATLAB incompetence

The countermeasures were taken and which ultimately proved to be good decisions for output of the

project. During each group meeting, risks analysis was done and tried to figure out the chances of

occurrence of the risk and if there is new risk. Usual countermeasures included plan adjustments,

finding alternative ways to complete the task and consulting the instructor of the project.

6.4. Project Meetings

According to available hours, work requirement, availability of Instructor and each member, the

schedule for meeting. The schedule for meeting is given in table 6.2

Table 6.2 Meeting hours per week.

anuary

Week 1 2hrs Week 12 2hrs

Week 2 2hrs Week 13 -

Week 3 2hrs

April

Week 14 1hr

Week 4 1hr Week 15 -

February

Week 5 - Week 16 2hrs

Week 6 1hr Week 17 -

Week 7 Exam Week

May

Week 18 2hrs

Week 8 2hrs Week 19 1hr

March

Week 9 - Week 20 1hr

Week 10 1hr Week 21 3hrs

Week 11 -

of 23

Group Meeting with Instructor

Group Meeting without Instructor

There were total 14 meetings were planned and 2 meetings were scheduled other than planned ones

during project and both were group meeting without instructor. Therefore, there were total 16

meetings. Agenda for each meeting was shared before the meeting and were followed in almost

every meeting. Project Manager was responsible for keeping notes for each meeting.

Other than project meetings, Communication using Email and WhatsApp group made life easy for

exchange of information and overall all these factors aided towards efficient working environment

for the project. There were suggestions to have meeting on every week but our group tried to utilize

those hours in working with project because there was continuous communication among the group

members but still there should be meetings in every week to keep checking the project status.

In addition, a couple of personal meetings with instructor or single group members were arranged

when problems with the task arise. Usually this was the case when single group member needed

more information regarding some subject of the project. These meetings also proved rather useful

and usually always advanced the project.

7. Discussion and Conclusions

The course was not only based on technical capabilities but also on the team work and management

skills as well as business aspect. This assigned project was based on the previous work and the

objective was to make improvements in the system. The project requires good skills in MATLAB,

Embedded Programming and Project Management. The MATLAB section of the project was tough

as compared to other tasks and Instructor helped us a lot in development of the project. The overall

project was good. Resulting Matlab program and how to use it can be found from the Appendix

(“Project code” and “3D EMF Map User Guide).

Other than technical aspects, we learned teamwork within multicultural environment, project

planning and execution has given a valuable experience and added to our skill levels. Other than

project management, we learned how to utilize a idea into business concept and what are the

necessary phases and skills required for entrepreneurship. And how to make our idea, a market

product. Documentation also played a key role while development of the project. It helped us

documenting every happening during the course of the work. Some lessons learned that how should

documentation can be done and what are the basic parameter for the documentation.

Overall the whole project which includes Technical Part, Management, Documentation and

Business Aspect Part. Every section has given some good lessons and it will help in professional

life. During the whole course, Project Instructor given us great insight related to all the aspects of

the project.

of 23

List of Appendixes

3D EMF Map User Guide

Notes of the 3D EMF Map code structure

Important Codes

Project Plan

Business Aspect Document

8. References

[1] L. Jukola, "Hybrid positioning and magnetic field measurement system," 2016.

of 23

Appendix A. 3D EMF Map User Guide

This is a guide for using Matlab based 3D magnetic field measurement tool 3D EMF Map.

Operation is descripted from system setup to conducting measurements and ending the operation.

To conduct measurements, you need Xbox’s Kinect camera, PicoScope 2000 series USB

oscilloscope (2406b used here), ELT-400 Exposure Level Tester from Narda (magnetic probe), two

Arduinos with wireless communication capabilities and computer to run Matlab. Here is 3D EMF

Map operation in step by step manner:

1. Set up hardware: Connect Kinect, PicoScope and the receiving Arduino to the computer

via USB. Also connect Narda probe to PicoScope’s channels A, B and C (probe’s x-axis

cable to channel A, y-axis to channel B and z-axis to channel C) and the sending Arduino to

a battery. Make sure the gyroscope is connected to the sending Arduino and attached to the

probe. The gyroscope axis must be aligned with Kinect and it must be kept very still in a

level position for roughly 11 seconds after turning it on. Turn on Narda probe and select the

sensitivity (for example 320 uT from “Mode” button and “High” from “Range” button).

2. Start the program: First start Matlab and there navigate to

“C:\Users\zbook\Documents\Hybrid positioning and magnetic field measurement

system\Measurement”. This folder contains all relevant files for measurements.

3. Conduct measurements: To start measuring run Matlab script “EMF_3D_Map_V1.m”.

This script runs the measurements automatically from start to finish. However, there are

some phases on measurements:

a. First the user must test Kinect operation. Matlab opens a window that displays video

stream from Kinect (both from camera and infrared camera) until someone enters

Kinect’s field of vision (measurer). After detecting a person, the stream freezes and a

skeleton is drawn over the person in picture as shown in figure 1. The picture can be

updated by pressing the left mouse button over the picture. The purpose of this test is

to adjust Kinect angle and make sure it can see the measurer and the measured target

all the time.

Figure A.1 Skeleton on Kinect testing window

of 23

b. To start the actual measurement, click right mouse button over the picture. The

Kinect window closes and the measurement starts. A small stop button also appears

which can be used to stop the measurement.

c. After the measurement time is up or the stop button is pressed the measurement stop

and script moves to data processing.

4. Data processing: Next the data is processed. Various spectrums are calculated and data

from different devices is united. In this phase, the script asks if the user wants to visualize

the measurement results.

a. First a window shown in figure 2 appears asking if user wants to draw a spectrogram

of the measurement.

b.

Figure A.2 Spectrogram question window

b. After that a window shown in figure 3 appears asking if the user wants to show a 3D

point cloud image of the measurements.

Figure A.3 3D point cloud image question box

c. Lastly the program will ask if the user wants to save the measurement data. Data is

saved to a Matlab file called “3D magnetic field data DateAndTime.mat” where

DateAndTime is the current date and time.

4. Ending the operation: The script will automatically close all the connected devises but

there is still a small problem that the user should be aware of: Drawing the 3D point cloud

image with this script apparently jams the Kinect/Matlab. This means that Matlab still works

but new measurement cannot be conducted until Matlab is restarted. Also Matlab for some

reason must be closed from the task manager after running the measurement script.

Important notes of the system:

Kinect can only recognize measurer when his/her face is towards the camera so make sure

the measurer faces it during the measurement!

Also, there should only be one person at time on Kinect field of view when measuring

of 23

System measures the position of probe as position of measurers right wrist so the measurer

should hold the probe on his/her right hand and from the round part rather than from the

actual handle (see figure 4)

The initial installation of PicoScope and Kinect is a lengthy process not descripted here so

use of our original computer is recommended

The “Measurement variables” part at the start of the measurement script

“EMF_3D_Map_V1.m” includes some useful variables for measurement (like measurement

duration) that can be changed as the user sees fit

Make sure the Arduinos have correct code installed (“Tracking_Gyro_Receiver “for

receiving and “Advanced_Gyro_Sender” for sending from folder

“C:\Users\zbook\Documents\Hybrid positioning and magnetic field measurement

system\Measurement\Hardware (Arduino)”)

Figure A.4 Correct way to hold the probe

of 23

Appendix B. 3D Notes of the 3D EMF Map code structure

Original code for this 3D magnetic field measurement device included Matlab, Python and Arduino

codes and an additional program for PicoScope that had to be ran separately. System operation also

included a lot of manual phases like starting programs and saving data. However, with this new

improved system only a single Matlab script is used to do all the measurements, data processing,

visualization and data capture. This makes the system much more user friendly and easier to adopt

for new users.

Even though the system is now easier to use it is still rather complex to modify. The main Matlab

code for example has around 800 lines of code and there are also couple of additional functions it

uses. Another reason for complexity is that the system uses internal methods of Kinect and

PicoScope through Matlab and their operation might be little tricky to figure out. However, the code

has been commented quite well which improves the learning process even though it still is rather

time consuming. This document also contains a brief explanation of the basic structure and some

notes of the system code to help with any future improvement of the system. For instructions to use

the measurement system refer “3D EMF Map User Guide”.

Appendix C. Important codes

Main script “EMF_3D_Map_V1.m”

The main code of the 3D EMF Map magnetic field measurement system is a Matlab script

“EMF_3D_Map_V1.m”. This script basically handles the whole measurement process and provides

a simple user interface. The code is divided to different blocks by measurement process phases. The

phases are: Hardware setup, Kinect test, Measurement, Data processing and Ending operation.

These blocks are also divided to smaller sub-blocks depending on their function. The most common

division is done by operating hardware (Kinect, PicoScope or Arduino). Usually the largest sub-

blocks deal with PicoScope operation.

To understand the code we briefly introduce the measurement operating principle. The

measurement system contains three measuring devices: Kinect, Narda’s magnetic probe and

gyroscope connected to Arduino. Kinect measures the position of the probe in 3D space, probe

measures strength of magnetic field and gyroscope orientation of the probe. In data processing part

different measurement quantities are tied together and used with each other.

Then back to the actual code. First block in the script simply connects each three devices (Kinect,

probe through PicoScope and Arduino) to Matlab using their internal methods (Kinect: Mex files,

PicoScope: dll libraries and Arduino simply uses serial connection). Many variables for

measurement are also set in this block. More information of devices internal operation can be found

on their respective documentation.

Second block uses only Kinect. In this block we test Kinect operation by showing video stream

from the device. Block has one main while-loop that updates the picture and checks if there is a

person in the Kinect field of view. When person is detected the automatic frame update stops and

of 23

next frame is shown only after clicking left mouse button as long as the person remains in the field

of view. To stop the test and start measurement right mouse button must be pressed.

Third block contains the actual measurement loop. Most of the loop contains PicoScope operation

for getting values for magnetic field (huge number of measurements with each loop iteration). At

the end side of the loop there are separate smaller sub-blocks for Kinect measurement (records the

position of users right wrist as x,y,z coordinate to an array) and Arduino/gyroscope measurement

(orientation as x,y,z value to an array). It should be noticed that there will be same number of

Kinect and Arduino measurements but several times more probe measurements. Therefore, the

single position and orientation corresponds to block of magnetic field values (certain time period)

since Kinect and Arduino are considerably slower measurement devices. This measurement loop

stops only when set time has passed or the generated stop button is pressed.

Fourth block contains all the data processing. First we get all the final probe data from PicoScope.

Then in the next sub-block we calculate a spectrum for each position-orientation pair from their

corresponding block of probe data with function “movingSpectrum”. After that the rest of the block

is basically visualization of data as spectrogram or 3D point cloud image from Kinect. There are

also additional visualization possibilities for raw data that are commented out but can be used if

needed. Last part of the block is for saving the measurement data for later use. System saves the raw

magnetic field data of each probe channel (channelAFinal, channelBFinal, channelCFinal), position

data from Kinect (hand_r), orientation data from Arduino (position), time points for each

position/orientation measurement point (time_f), measurement starting time (Tstart), point cloud for

later visualization (ptCloud) and the spectrum arrays of the measurement mentioned earlier

(FsignalA0, FsignalB0, FsignalC0). Data is saved to file which name includes measurement date

and time.

The last block in the script only disconnects all the devices and deletes the device objects.

movingSpectrum

movingSpectrum is a Matlab function used to calculate spectrum for each position/orientation pair

or time point. Single spectrum is calculated from part of final magnetic field data using the

measurement time points (time_f in main code). Basically function takes probe data with the size of

one time step and calculates the spectrum with fft then moves on by length of time step and

calculates the next spectrum. This continues until all probe data is dealt with. There is also option of

choosing the time window used in spectrum calculations. Finally the function returns an array that

has all the calculated spectrums (Fsignal) and some other values like down sampled signal.

Tracking_Gyro_Receiver

Arduino code for receiving Arduino. This code includes receiving wireless transmission from the

transmitting Arduino with the gyroscope. In addition the code sends the received data to computer

via serial port from where Matlab can later read it.

Advanced_Gyro_Sender

Arduino code for sending Arduino with the gyroscope. This code includes operating the gyroscope

and wireless data transmission to the receiving Arduino. Basically it sets up the gyroscope and

of 23

wireless link and starts operation and transmission if no error occurs. Gyroscope operation requires

that correct library files are present as mentioned at the beginning of code.

Other files

System runs with these codes but devices use several internal methods when to run in Matlab.

Kinect uses Mex files to convert operation from C++ to Matlab (originate from Kinect SDK),

PicoScope uses dll libraries and parts from PicoSDK, PicoScope Support Toolbox and PicoScope 6

program and Arduino uses some external libraries. Therefore, using the measuring system on other

new computers requires quite much installation and struggling. More information of these can be

found from kin2-user-guide (Kinect) and picotech’s websites (PicoScope).

Faults and improvement suggestions

Even though measuring system works and is much easier to use compared to before there are still

some faults. First of all Kinect freezes for some reason after the measurement. More precisely you

can only take one point cloud image with it and then it throws an error when trying to take new one.

This prevents consecutive measurements and Matlab needs to be restarted between measurements.

Even though Matlab does not freeze the freezing of Kinect prevents closing Matlab normally and

also deleting some variables. Therefore, Matlab must be closed using task manager.

Other regrettable issue was orientation measurement implementation. Communication between

Matlab and Arduino works on separate code (see script “Arduino_to_Matlab” for example) but for

some reason the same communication won’t work when implemented into EMF_3D_Map_V1.

This issue is somewhat severe and was noticed too late to fix. Apparently “Measurement” loop in

the code (sub-block “Arduino measurement”) tries to read serial port infinitely and measurement

gets stuck there.

Other minor issues that affect usability more than actual operation include gathering variables to

one place and otherwise making parameters easier to change. At the moment almost all parameters

like PicoScope sampling frequency and range must be manually changed from somewhere (usually

set up block) from the code using device’s own syntaxes. Some sort of control window would be

ideal for changing the parameters.

Another minor issue is the length of the code. The main script is over 800 lines long and some of

the parts could be implemented as their own functions. The main reason why most of the code is in

single script is that devices need to use their internal methods to operate. Therefore, dividing code

to functions would require passing considerable amount of input and output variables. Though this

issue does not affect the operation of the system it could make the system simpler and more

manageable.

One of the biggest issues during the coding process of the measurement system was the

implementation of parallel measurement of devices. Ideally all the measuring tools would run in

parallel so that the measurement would be conducted continuously at the same time. However,

implementing this on Matlab proved rather difficult. Matlab does not offer right tools for running

measuring loops in parallel or swift interaction with different parallel elements. Although Matlab

does have some parallel processing capabilities (parpool, spmd) they are more useful for processing

of 23

existing data and do not offer any possibility for interaction with the user. Even worse problem was

that Matlab’s parallel processing severs the connection to hardware devices. Thus, the processing in

our system is not actually parallel but all three measurements are done in series during each loop

iteration. This still gives correct values but might affect the phase of magnetic field measurement.

One future prospect could be implementing parallel measurement with Simulink or using other

coding languages.

The system also still needs more testing. There are many situations where the system might act

unexpectedly like when the Kinect loses sight of the measurer or when there are more than one

person in Kinect’s field of view and many others.

Last improvement could be implementing memory allocation of the system so that it can measure as

long as needed without any set maximum measuring time. This could make measurement smoother

since now best way to do this is to set measuring time very long and simply push stop button when

user wants to quit.