Introduction - Vanderbilt University



Wii System Components to Track Ultrasound Probe and Create 3-D Images

Investigators: Van Gambrell, Laura Owen,

Steven Walston, Jonathan Whitfield

Advisor: Christopher Lee, M.D.

Date Completed: April 27, 2010

ABSTRACT

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that progressively destroys motor neurons and causes atrophy in skeletal muscle. The goal of our project is to integrate an ultrasound imaging method with tracking techniques from Nintendo’s Wii system to obtain accurate skeletal muscle volume measurements. Three tracking systems were created each returning x, y, and z location along with roll, pitch, and yaw angle orientation. One system involved the IR camera tracking an LED array, the second system added the WiiMotionPlus to return yaw, pitch and roll, while the third system used the accelerometer from a WiiMote to give x, y, and z with the WiiMotionPlus. The data from each system was then implemented into a program that aligned and rotated every US slice to give a final 3-D reconstructed image. The error from all three systems was greater than the error of the US machine, producing unusable 3-D images. A more accurate tracking system could be implemented to improve results.

INTRODUCTION

Amyotrophic Lateral Sclerosis (also referred to as ALS or Lou Gehrig’s Disease) is a neurodegenerative disease that currently affects 20 - 30 thousand people in the United States. The disease targets and progressively destroys spinal motor neurons that stimulate skeletal muscles [1, 2]. Muscle fibers require neural stimulation to maintain strength and structure. As a result of ALS, the damaged spinal neurons and their respective nerve fibers are unable to send signal impulses to muscle, effectively causing the atrophy of muscle [3, 4]. This phenomenon is diagramed in Figure 1. As the disease progresses, more neurons become diseased and waste additional skeletal muscle fibers. Over time, what was once full, normal muscle atrophies into a thin, weak strain of fibers.

The full body degradation of muscles eventually causes semi or full paralysis in patients accompanied by speech, breathing, and swallowing problems. Respiratory and pneumonia problems associated with ALS are the main reasons newly diagnosed patients are normally given just 3-5 years to live [5]. With approximately five thousand new diagnoses each year, there is a necessity for research in the topic [1]. Understanding the effects of ALS should aid in increasing the life expectancy of patients, with a long term goal of finding a cure.

Dr. Christopher Lee specializes in evaluating muscle ultrasound images of ALS patients in the Vanderbilt University Medical Center’s Neurology Department. He uses the information gathered to determine early clinical and electrodiagnostic features of critical illness polyneuropathy and myopathy. Dr. Lee’s current studies involve using the effect of atrophy in the muscles to gauge the progressed state of the disease in individual patients. The volume and shape of easily identifiable muscles like the bicep are measured over periods of months to observe differences brought on by the ALS disease.

Currently, the optimal method for measuring muscle volume is using Magnetic Resonance Imaging (MRI) [6]. This technique is the gold standard in image quality, but there are several factors that make MRI a difficult method for imaging ALS patients.

One issue with MRI is the high acquisition and operational costs of the machine. Typical MR machines run at approximately $3 million, a steep price for specialized clinics to be expected to fund. Operational costs vary depending on the size and strength of the magnet, but are usually high to cover the cooling process. A cheaper alternative would allow more patients to be seen and larger research projects to be conducted each year.

A second difficulty for ALS research conducted on MRI equipment is the relatively long acquisition times of approximately 30 minutes. Patients with ALS are prone to having uncontrollable muscle contractions or spasms that would reduce image quality if occurring during the acquisition time [7]. An imaging technique that uses a reduced time necessary for acquisition would benefit the image quality and patient stress.

A similar set of problems facing the use of MRI to image ALS patients is the immobile nature of the machine and its round bore. It can become difficult for people with ALS to move around and change positions in later stages of the disease as they near paralysis [7]. The lack of mobility in the patient means a portable imaging technique would better serve to ease the task of participating in research for the patient. Most MRI machines use round bores that require patients to lie prostrate for the full image acquisition time. Again, this is an issue for those patients whose disease has progressed to local or full paralysis and cannot easily lie down in the machine. There are MR designs with open bores, but they too require the patient to be flat in the machine. A technique for measuring muscle volume that does not include having the patient become uncomfortable due to movement or position would enhance the effectiveness of the research.

Overall, there is a need for a low cost, mobile, and fast method for accurate muscle volume measurements that accommodates the needs and restrictions of ALS patients. Ultrasound (US) is an alternative imaging technique and has been shown to give accurate muscle volume measurements, compared to MRI [8]. The machine used in this design, the Sonosite Titan, is much cheaper than an MRI machine at the relatively low cost of $17,000 [9]. The Titan machine is mobile, with a portable docking station, and is compatible with a laptop for data collection and analysis [10]. Ultrasound imaging is much faster than MRI, with imaging times remaining less than a minute, as reported by Dr. Lee.

The Nintendo Wii system uses infrared light and accelerometers to track the gaming controllers. Our design uses these qualities of the system to attempt to track the ultrasound probe as it acquires muscle images. The goal of our project is to integrate the ultrasound imaging method with tracking techniques from Nintendo’s Wii system to obtain accurate skeletal muscle volume measurements.

METHODOLOGY

System 1: WiiMote Tracking Four Infrared LEDs

Two WiiMotes were attached to individual goniometers using Velcro, and placed on a stable flat surface such that the centers of the WiiMote cameras were at a known orientation (55°), and distance apart (36”). Each WiiMote has a viewing angle of 41° and 31° in the horizontal and vertical axes, respectively [15]. The WiiMotes were paired to the computer via a USB bluetooth adapter. The infrared camera, accelerometer, and button status information were all parsed by the WiiLab MATLAB program [16].

The four 935nm infrared LEDs were mounted onto the circuit in a square arrangement as diagramed by the schematic in Figure 2, such that each side of the square was 1 inch. The LEDs have an emission angle of 90°. The prototype for the LED tracking module is shown in Figure 3. The module was then attached to the flat surface of the US probe with the LEDs being closer to the transducer. While testing, the prototype was oriented to face toward the WiiMotes.

Executing the bothwiimotes() function within WiiLab ran the LED triangulation and orientation software and initialized the US video feed, which was connected to the laptop via a S-video-to-USB converter. The triangulation software is based on the trigonometry of Figure 4.

Each WiiMote can simultaneously track up to 4 LEDs so the position of each LED was triangulated independently. Because the initial LED assignment order to the WiiMote was dependent on the order in which the WiiMote detected the LEDs it was essentially a random assignment each time the program was initialized. To institute some consistency in the assignment and correspondence between the WiiMotes, an LED assignment code was written to align the WiiMote LED registration with the LED location in space.

Knowing the WiiMote LED registration and the LED location in 3D, the orientation of the prototype and therefore the probe could be determined. Projecting through the xy, xz, and yz planes, the angle between 2 LEDs spatial location provided the orientation of the prototype with regards to each respective plane.

System 2: WiiMotionPlus and Wiimote Linear Accelerometer System

The second system we proposed employed the 3-axis linear accelerometers from the Wiimote used in conjunction with the 3-axis rate gyroscopic accelerometer data from the WiiMotionPlus to, in theory, provide the full six degrees of freedom needed to accurately track the US probe in 3-D space. The Wiimotes ADXL-330 3-axis accelerometer is used by the Wii system to estimate the yaw, pitch and roll angle of the Wiimote in relation to the Wii system’s infrared source (Figure 6). The accelerometer data was fed into MATLAB via the Wiimote’s Bluetooth transmitter. To obtain linear position data in 3-D space, the Wiimote accelerometer incoming data had to be integrated twice using numerical integration techniques in MATLAB. The Wii-Motion+ uses the InvenSense IDG-600 two axis rate gyroscopic accelerometer to provide the rates of change in yaw, pitch and roll.

The incoming data was read into MATLAB via an Arduino prototype board with a USB connection (Figure 7). To obtain yaw, pitch and roll angle from the Wii-Motion+ the incoming data had to be properly scaled and integrated using numeric integration techniques in MATLAB. The scaling was determined by repeatedly moving the WiiMotionPlus a known angle on each axis of rotation and scaling the incoming data appropriately. Both the Wiimote and WiiMotionPlus were securely attached to the US probe. Due to a computational error this device was not tested in full.

System 3: WiiMotionPlus and LED Tracking

The final system we designed employed the LED tracking system to provide linear position in 3-D space and the rate gyroscopic accelerometer data from the Wii-Motion+ to provide angular position. Two Wiimotes were used to track the IR array. The IR LED array and WiiMotionPlus were attached to the face of the US probe.

Phantom

To validate our method of measuring volume, we designed a phantom to be used by both the Sonosite Titan and a 4.7T small animal MRI machine. The phantom consisted mostly of a gelatin and psyllium concoction that has been used in previous studies to represent tissue in US images [17]. A straw was used to create an air bubble in the gel to provide an easily identifiable volume of space to be measured by the two techniques.

3-D Reconstruction Software

            In order to re-create the ultrasound data, each image needed to be associated with its correct location and orientation.  The use of the synchronized data acquisition technique makes this simple.  Every slice was numbered according to order during data acquisition, as well as every data point and angle.  In order to translate the data so that it represented the scanned area, an empty three dimensional matrix needed to be created that represented the size of the arm.  The Sonosite Titan images were created using approximately 82 pixels per centimeter.  Initially, the program asked for the dimensions, length, width, and depth of the arm in centimeters.  From here the arm dimensions were multiplied by the 82 pixels per centimeter to give the appropriate number of pixels to represent the arm without distortion.  In addition to the empty patient matrix, an empty temporary matrix and an empty count matrix of equivalent dimensions were created.  Since the system returned the position data as a relative number, the data was normalized with the arm dimensions.  After all the data had been appropriately scaled, one slice at a time was stored in the temporary matrix according to its x and y location.  The top center point of each slice represented the actual location denoted by x and y.  After being translated, the slice was then rotated according to the yaw, pitch, and roll angle.  The program returned 3 matrices of the same size as the slice, but instead of holding intensity values, each held the new x, y, or z location.  Given these new locations, the original intensity value was stored in the patient matrix.  Every time a data point was stored in a particular voxel, it was noted in the count matrix.  After the completion of the program, the patient matrix was divided by the count matrix to give an average intensity value at every location.

RESULTS

LED System

Following tracking, MATLAB was used to create a three dimensional plot of location. This plot included the location for each LED and appeared as though the tracking was working. Figure 8 shows the x, y, and z data returned from an ultrasound scan of the phantom. The data included a lot of noise so it was filtered using a 13 point low-pass digital filter. The scan returned 149 data points. As seen below the y data appears as if correct, because the scan remained still in this dimension. When looking at the x data however it appears incorrect because the motion involved a gradual decline along the x dimension. The z data look approximately correct however seem to still have a decent amount of noise. The z motion of the probe started at an initial location moved towards the IR detector, and then returned along the same path. When observing the angle data, the roll and pitch angles appear correct because they remain within 20 degrees of motion. The yaw however reaches angles of -80 degrees, this is obviously incorrect because the probe was never oriented at large angles.

In order to test the accuracy of the LED tracking system the device was moved along a fixed path. The data returned was then compared to the known data. This error is shown in Figure 9. The error is consistent with the data and observations from the ultrasound scan. Surprisingly, the greatest error shown is in the y data. This could be a result of the non-uniformity between the two IR cameras. A difference here could cause the Y position to remain constant when it is actually changing. The x error follows what was observed from the US scan. The z error is within range for the design specifications. Unfortunately, because the x and y error is greater than that of the ultrasound system the tracking system fails to meet the standards needed to reproduce accurate images.

LED + Wii MotionPlus System

The tracking method that returns x, y, and z data is the same as in the above system and returned the same error shown in Figure 9. This system incorporated the WiiMotionPlus instead to return the orientation angles. Figure 10 shows each angle, roll, pitch and yaw stays within ±30 degrees, which approximately corresponds with the orientation of the probe during the scan. The reliability of these measurements is only good for acquisition times of up to 15 seconds. This is a result of the drift of the WiiMotionPlus shown in Figure 11. In the future drift could be controlled by periodically orienting the device in the vertical position and re-zeroing the WiiMotionPlus angle values.

3-D Reconstruction Software

  There were several limitations involving the 3-D reconstruction.  The first was a result of the amount of data that was being handled.  When trying to reconstruct using all the data, the MATLAB memory would become completely occupied.  Clearing the variables once they were used in an attempt to reduce the memory constraints were tested to no avail.  Eventually, the images had to be resized to be smaller in order to reduce the amount of data being processed.  After the reconstruction was completed, the images contained some intensities but with no distinguishable figures.  This is most likely a result of the error produced by the tracking system, but could also be a result of the resolution reduction for data processing.  In the future, this issue could be dealt with by using C based programming to reduce memory constraints or by using a more accurate tracking system.

The program does not calculate a volume yet, but it could be done by tracing the muscle in each slice using the roipoly function in MATLAB.  After each region of interest is selected it eventually could be patched and the surface of the muscles rendered through the isosurface command in MATLAB.  In order to determine volume, the voxel dimensions must be multiplied by the size of the surface matrix.  The error produced by the tracking system and the MATLAB memory limitations indicate that the new slices did not accurately represent a single vertical slice from the ultrasound machine.  This resulted in the images not being able to specify the muscle region; therefore the volume analysis was not performed.  Possible future solutions would also include using C programming to reduce memory limitations and using a more accurate tracking system.

Overall the design incorporates cheap components for a low cost and portable system. As seen in Figure 12, the device is small and easily attaches to the Sonosite Titan. Unfortunately, the desire to keep costs at a minimum compromised the quality of the overall system.

|Component |Unit Price |Quantity |

|Wii-Mote |$39.99 |2 |

|Wii-Motion+ |$17.96 |1 |

|Arduino |$29.99 |1 |

|Arduino-WiiMotionPlus Adapter |$4.00 |1 |

|Infrared LEDS |$1.25 |4 |

|Resistors, Batteries, Wires |$10.00 |1 |

|Goniometers |$10.00 |2 |

|USB Video Capture Cable |$39.99 |1 |

|Phantom Construction |$8.50 |1 |

|TOTAL: |$215.42 | |

CONCLUSIONS

The overall goal of the design was to create low cost and portable ultrasound system that allowed for the monitoring of muscle degradation over time as a result of amyotrophic lateral sclerosis. While the system was able to keep costs at a minimum, the quality of the images for reconstruction suffered. In order to create 3-D images without compromising quality, the error of the tracking system needed to be less than or equal to the error of the image acquisition system, in this case the Sonosite Titan. Unfortunately, the linear error in the X and Y direction exceeds the linear error from the ultrasound system. This means that the system is unable to provide an accurate muscle volume measurement for the patient and our goal is not met.

RECOMMENDATIONS

In the future, this design could incorporate more accurate methods of tracking. Using high grade accelerometers and gyroscopes would be the most accurate method for tracking but would increase costs substantially. Another method that could be implemented would be the optical tracking sensor from a computer mouse. This could potentially increase accuracy immensely while keeping costs at a minimum. The concepts of this design are substantial, but the technologies available for the cost have limited its capabilities.

REFERENCES

[1] “Multiple Sclerosis and Amyotrophic Lateral Sclerosis-Related Projects.” Ongoing and Completed Projects, Health Investigations Branch, Division of Health Studies. CDC: Agency for Toxic Substances and Disease Registry, 14 May 2003. Web. 22 Apr 2010. .

[2] Boillée S, et al. (2006) Onset and progression in inherited ALS determined by motor neurons and microglia. Science 312:1389-392.

[3] Rowland, Lewis P., and Neil A. Schneider. “Amyotrophic Lateral Sclerosis.” New England Journal of Medicine 344.22 (2001): 1688-700. Web. 25 Apr 2010.

[4] Lynch, G. S. (2001) Therapies for improving muscle function in neuromuscular disorders. Exerc. Sport Sci. Rev. 29, 141-48.

[5] Kaplan LM, Hollander D. Respiratory dysfunction in amyotrophic lateral sclerosis. [Review]. Clin Chest Med 1994; 15: 675-81.

[6] Mitsiopoulos, N. et al. “Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography.” Journal of Applied Physiology, 85. (1998): 115-122.

[7] “Amyotrophic Lateral Sclerosis Fact Sheet.” National Institute of Neurological Disorders and Stroke. NIH, 15 Mar 2010. Web. 25 Apr 2010. .

[8] Esformes, Joseph I., Marco V. Narici, and Constantinos N. Maganaris, “Measurement of human muscle volume using ultrasonography,” European Journal of Applied Physiology. 87.1 (2002): 90-92.

[9] “Sonosite Titan Portable Ultrasound Machine.” Absolute Medical Equipment. Absolute Medical Equipment, 2009. Web. 25 Apr. 2010. .

[10] “Titan,” . SonoSite, 2010. Web. 25 Apr 2010. .

[11] Juha P. Ahtiainen, Merja Hoffren, et al. (2009) Panoramic ultrasonography is a valid method to measure changes in skeltal muscle coss-sectional area.  European Journal of Pplied Physiology.

[12] Lee Barber, Rod Barret, Glen Lichtwark (2009) Validation of a freehand 3D ultrasound system for morphological measures of the medial gastrocnemius muscle.  Journal of Biomechanics 42:1313–1319.

[13] Luigi Gallo, Giuseppe De Pietro, Ivana Marra (2008) 3D interaction with volumetric medical data: experiencing the Wiimote. ICST

[14] Thomas J. MacGillvray, Erin Ross, et al. (2009) 3D freehand ultrasound for in vivo determination of human skeletal muscle volume. Ultrasound Med Biol 35(6): 928-935.

[15] Simon Hay, Joseph Newman, Robert Harle. Optical Tracking Using Commodity Hardware.  Digital Technology Group, Computer Laboratory, University of Cambridge.

[16] Jordan Brindza, Jessica Szweda. Wiimote Interactions for Freshman Engineering Education. University of Notre Dame

[17] Kendall, John L., and Jeffery P. Faragher. “Ultrasound-guided central venous access: a homemade phantom for simulation.” Canadian Journal of Emergency Medicine 9.5 (2007): 371-73. 26 Apr 2010.

[18] A. M. Goldsmith, P. C. Pedersen, T. L. Szabo. (2008) An Inertial-Optical Tracking System for Portable, Quantitative, 3D Ultrasound. IEEE International Ultrasonics Symposium Proceedings. 45-49.

APPENDIX

Innovation Workbench

Ideation Process

Innovation Situation Questionnaire

1. Brief description of the problem

There is a need for a low cost, portable 3D imaging modality to assess muscle shape and structure.

2. Information about the system

2.1 System name

Infrared Camera from Wii System to Track Ultrasound Probe to Create 3-D Image

2.2 System structure

[pic]

2.3 Functioning of the system

The primary function of this system is for the tracking of the LEDs by the infrared camera within the Wiimote.

The purpose of the function is to know the location of the transducer for specific images acquired. this will allow for the 3-D reconstruction of several images.

The Wiimote infrared camera will be mounted and the LEDs will be attached to the transducer, the infrared camera will track the transducer in real time. The location will provide accurate information that will be implemented into of 3-D image creation software that will give real time 3-D images of muscles and other organs.

2.4 System environment

Many different energy sources exist in the environment surrounding the infrared camera, these energy source may cause error reading from the camera which would then throw the data off. Additionally, mirrors in the surrounding area may reflect the LED transducer signal, which could be picked up by the camera as well acting as another source of error.

3. Information about the problem situation

3.1 Problem that should be resolved

A low-cost and portable method for taking 2-D ultrasound images and creating an accurate depiction of the muscle in 3-D.

3.2 Mechanism causing the problem

The mechanism that is causing the problem is the accuracy of the tracking device. These images are acquired in a freehand manner therefore there currently is no way to standardize images that are taken over long periods of time. Therefore, when comparing an image from one scan to an image from another scan it is difficult to discern if the image is of the same location in both scans.

3.3 Undesired consequences of unresolved problem

There are many undesired consequences of this problem. When comparing the two images as the same, the data of quantitative muscle atrophy will be off if the images are not of the same area of muscle. Additionally, having in accurate location of the transducer for image reconstruction will cause the 3-D image to be skewed or disproportional.

3.4 History of the problem

This has been a major issue in 3-D ultrasound in the past. The inaccuracy of the tracking devices currently implemented do not allow for accurate 3-D images. Without accurate 3-D images there is no advantage of this system. The problem has been addressed in the past by using other tracking devices but one issue has been that as the device get more accurate, the cost goes up. Again, as cost increases, the advantage of this system over MRI decreases.

3.5 Other systems in which a similar problem exists

In MRI a similar issue exists, when only taking local images. If analyzing muscle atrophy over time, typically on a small region of interest is scanned. Again this makes it difficult to ensure the comparison of the same area of muscle. This has been rectified in MRI scan by taking full limb and body scans. This provides length data as a reference, therefore the muscle can be accurately identified through its vicinity to the top or bottom of the limb.

3.6 Other problems to be solved

Some other problems that may need to be solved are the accuracy of the Wiimotes. Another problem could be the compute time from the tracking to the reconstruction.

4. Ideal vision of solution

The tracking device that causes the return of inaccurate results is removed from the system.

5. Available resources

Time Resources: Concurrent operations could readily aid our design in success. If the tracking device and 3-D reconstruction are able to work simultaneously, then the system could work in a real-time manner. this would aid not only in volumetric return, but could eventually aid in a surgical setting.

Field Resources: Infrared light energy is harnessed for the tracking of the transducer.

6. Allowable changes to the system

Drastic changes to the system are allowed.

Specifically, the tracking modality could be changed to improve accuracy.

However, the 3-D reconstruction software is standard for all different imaging modalities and could not be drastically changed.

7. Criteria for selecting solution concepts

Some success criteria are the accuracy for the tracking software. The accuracy should be within 1 mm, therefore the accuracy of the final 3-D image will be within 1 mm^3.

8. Company business environment

Nintendo: It is a company that focuses on the production and design of video games. The company was able to create a cheap infrared camera that is provides extremely accurate position data.

Sonosite: A company that focuses on creating imaging modalities. Provided us with the Titan an inexpensive and portable Ultrasound machine which can be readily implemented with the tracking devices.

9. Project data

Name: Infrared Camera from Wii System to Track Ultrasound Probe to Create 3-D Image

Objectives: Create and accurate tracking software, adapt a 3-D reconstruction software to our position data, and acquire muscle data to verify our results.

Timeline: Tracking device: February 1, 2010. 3-D Software Adaptation: March 1, 2010. Data Collection: April 1, 2010. Data Analysis: April 7, 2010

Problem Formulation

1. Build the Diagram

[pic]

2. Directions for Innovation

12/8/2009 11:28:00 PM Diagram1

1. Find a way to eliminate, reduce, or prevent [the] (ALS) in order to avoid [the] (Destruction of neurons).

2. Find a way to eliminate, reduce, or prevent [the] (Muscle Atrophy) in order to avoid [the] (Progression of disease), under the conditions of [the] (Destruction of neurons), then think how to provide [the] (2D Ultrasound Imaging).

3. Try to resolve the following contradiction: The harmful factor [the] (Muscle Atrophy) should not exist in order to avoid [the] (Progression of disease), and should be in place in order to provide or enhance [the] (2D Ultrasound Imaging).

4. Find a way to eliminate, reduce, or prevent [the] (Destruction of neurons) in order to avoid [the] (Muscle Atrophy), under the conditions of [the] (ALS).

5. Find an alternative way to obtain [the] (2D Ultrasound Imaging) that offers the following: provides or enhances [the] (3D US Mapping from freehand imaging), does not require [the] (Muscle Atrophy).

» 6. Find an alternative way to obtain [the] (3D US Mapping from freehand imaging) that offers the following: provides or enhances [the] (Therapy), does not require [the] (2D Ultrasound Imaging) and (Probe Tracking).

» 7. Find an alternative way to obtain [the] (Probe Tracking) that provides or enhances [the] (3D US Mapping from freehand imaging).

8. Find a way to eliminate, reduce, or prevent [the] (Progression of disease) under the conditions of [the] (Muscle Atrophy).

9. Find an alternative way to obtain [the] (Therapy) that offers the following: eliminates, reduces, or prevents [the] (Progression of disease), does not require [the] (3D US Mapping from freehand imaging).

Prioritize Directions

1. Directions selected for further consideration

8. Find a way to eliminate, reduce, or prevent [the] (Progression of disease) under the conditions of [the] (Muscle Atrophy).

8.1. Isolate the system or its part from the harmful effect of [the] (Progression of disease).

8.2. Counteract the harmful effect of [the] (Progression of disease).

8.3. Impact on the harmful action of [the] (Progression of disease).

8.4. Reduce sensitivity of the system or its part to the harmful effect of [the] (Progression of disease).

8.5. Eliminate the cause of the undesired action of [the] (Progression of disease).

8.6. Reduce the harmful results produced by [the] (Progression of disease).

8.7. Apply universal Operators to reduce the undesired factor (Progression of disease).

8.8. Consider resources to reduce the undesired factor (Progression of disease).

8.9. Try to benefit from the undesired factor (Progression of disease).

6. Find an alternative way to obtain [the] (3D US Mapping from freehand imaging) that offers the following: provides or enhances [the] (Therapy), does not require [the] (2D Ultrasound Imaging) and (Probe Tracking).

6.1. Improve the useful factor (3D US Mapping from freehand imaging).

6.2. Obtain the useful result without the use of [the] (3D US Mapping from freehand imaging).

6.3. Increase effectiveness of the useful action of [the] (3D US Mapping from freehand imaging).

6.4. Synthesize the new system to provide [the] (3D US Mapping from freehand imaging).

6.5. Apply universal Operators to provide the useful factor (3D US Mapping from freehand imaging).

6.6. Consider resources to provide the useful factor (3D US Mapping from freehand imaging).

7. Find an alternative way to obtain [the] (Probe Tracking) that provides or enhances [the] (3D US Mapping from freehand imaging).

7.1. Improve the useful factor (Probe Tracking).

7.2. Obtain the useful result without the use of [the] (Probe Tracking).

7.3. Increase effectiveness of the useful action of [the] (Probe Tracking).

7.4. Synthesize the new system to provide [the] (Probe Tracking).

7.5. Apply universal Operators to provide the useful factor (Probe Tracking).

7.6. Consider resources to provide the useful factor (Probe Tracking).

2. List and categorize all preliminary ideas

* Wiimote accuracy

* 3D position data of US probe, from Wiimote

* Reference point for muscle measurements

* 3D reconstruction

* Adaptation of reconstruction software with tracking data

Develop Concepts

1. Combine ideas into Concepts

* Accuracy of the reconstructed model

* Position and direction algorithms

* Accurate reconstruction of muscle

2. Apply Lines of Evolution to further improve Concepts

Building a bi-and poly- system with the Wiimotes to increase accuracy

Increasing controllability through methodical US scans

Evaluate Results

1. Meet criteria for evaluating Concepts

Criteria: Must be within in 1 mm^3 of accuracy with the final 3-D image

2. Reveal and prevent potential failures

A potential failure is the tracking device malfunctioning or not being able to provide accurate enough data.

3. Plan the implementation

Critics will want validation of the accuracy. This can be obtained by comparing the newly created images with the gold standard of MRI models.

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[pic]

Figure 1. Diagram of normal and ALS affected muscle and neural system

A. B.

[pic] [pic]

Figure 8.A.Shows filtered position data returned from the LED tracking system in relative position. B. Shows filtered angle data returned from the LED system in degrees.

A. B.

[pic] [pic]

Figure 10.A.Shows filtered position data returned from the LED+WiiMotionPlus tracking system in relative position. B. Shows filtered angle data returned from the LED+WiiMotion Plus system in degrees.

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Figure 11. Shows the drift of the Wii motion plus, with movement only occurring between 17-24 seconds

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Figure 9. Shows the percent error of the LED tracking system, specific for each dimension.

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Figure 7. Wii-Motion+ with InvenSense IDG-600 rate gyroscopic accelerometer labeled with an arrow

x

Y

Z

[pic]

Figure 6. The Wii-motes internal circuit board with the ADXL-330 3-axis accelerometer’s axes of acceleration labeled.

[pic]

Figure 2. Circuit schematic for powering the 900nm LEDs.

[pic]

Figure 3. LED tracking prototype board.

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Figure 4. Diagram corresponding to triangulation calculations.

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Figure 5: Equations used to determined LED position.

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Figure 12. All system components with the Sonosite Titan US Machine.

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