Final Presentation

Team BIA

Overall Goal of Project

• Bioelectrical impedance analysis (BIA) works by measuring the rate at which a low-level fixed frequency electrical current passes through the body
• The current passes through the body by means of electrodes placed on the body parts and the voltage drop is measured.
• By determining the resistance to the flow of the current, body fat percentage is estimated, which is a more accurate representation of a person’s nutritional state [1].
• A higher body fat percentage can be an indicator of an increased risk of potential life altering diseases such as diabetes and heart issues [2].
• Current methods are inaccurate, non-portable, and can be expensive [3].
• Goal: Develop a smaller scale BIA analysis for at-home use that is inexpensive and accurate

Existing Technology & Shortcomings

• Skinfold Calipers [4] [5]
• Poor self-administration

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• Body Circumference Measurements [6]
• Inaccurate Equations

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• Hydrostatic Weighing [7] [8] [9]
• Inaccessible for general public

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• BIA Scales & Handhelds
• Not accurate for all demographics
• Accurate BIA devices are costly

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https://nutritionalassessment.mumc.nl/en/skinfold-measurements

Initial Measurements

Circuit Development

• Schematic [10] [11] [12]
• Safety
• Noise Reduction
• Sensitivity
• Initial Breadboard
• Fixes and Changes
• Final Breadboard

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Initial Iteration

• The breadboard circuit was used in our testing
• Battery powered circtuitry was put on a protoboard to isolate from the rest of the circuit
• Two electrodes are placed on the right leg and wrist of the patient

Data Collection

Final Implementation

Results

Packaging

• The packaging was 3D printed using a Markforge printer with black Onyx material.
• The edges of the packaging were fileted to ensure there were no sharp edges.
• The size was also minimized to ensure that the device was portable

Packaging Continue

• The packaging is split into two parts.
• There are four pegs on the upper part and it contains the opening for the LCD.
• There are also slots for the arduino USB cable and the electrodes.

Disassembled View of Device

Validation of Circuit with Resistor

• The first validation test used a 620kΩ resistor to stimulate the average resistance of a human body.
• Change was observed between the input signal from the microcontroller and the output of the circuit, demonstrating the resistance has an effect on the output.

Validation of the circuit with Participants

• Validation testing was also performed on group members in order to determine the reproducibility of the results from the earlier circuit.

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MATLAB Regressions

• MATLAB multivariate linear regression function, mvregress()
• Inputs:
• X matrix (n-by-3) containing age, weight, and analog reading for n data points
• Y matrix (n-by-1) containing body fat percentage for the given x data
• The Y matrix is found using the Omron Healthcare Body Fat Analyzer shown in slide 3.
• Output:
• 3-by-1 matrix with independent variable coefficients
• Data collected from team members
• 13 unique data points collected for male regression
• 21 unique data points collected for female regression

Male Body Fat % = -0.299669*age + 0.3624*weight - 0.0078*analogReading

Female Body Fat % = -0.0698*age + 0.1415*weight - 0.002*analogReading

Future Work

• MATLAB Regressions
• Increase test subject pool to create more accurate regressions for males and females
• Printed Circuit Board
• We developed a PCB design so this project can be reproduced and improved upon

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Conclusion

• Reviewed current methods of bioelectrical impedance analysis
• Created a lightweight and easy-to-use BIA device that allows individuals to measure their body fat percentage
• Current design and proposed future developments offer compact packaging for the electronics and display
• Mathematical regression used to calculate body fat percentage has the ability to be easily updated to provide more accurate results

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References

[1] A. Walter-Kroker, A. Kroker, M. Mattiucci-Guehlke, and T. Glaab, “A practical guide to bioelectrical impedance analysis using the example of chronic obstructive pulmonary disease,” Nutrition Journal, vol. 10, no. 1, 2011.

[2] A. Böhm and B. L. Heitmann, “The use of bioelectrical impedance analysis for body composition in epidemiological studies,” European Journal of Clinical Nutrition, vol. 67, no. S1, 2013.

[3] Wells JCK, Fewtrell MS, "Measuring body composition," Archives of Disease in Childhood, vol.10, no. 1, 2006.

[4] “Simple measures - skinfolds,” DAPA Measurement Toolkit. [Online]. Available: https://dapa-toolkit.mrc.ac.uk/anthropometry/objective-methods/simple-measures-skinfolds. [Accessed: 14-Feb-2022].

[5] A. S. Jackson and M. L. Pollock, “Practical assessment of body composition,” The Physician and Sportsmedicine, vol. 13, no. 5, pp. 76–90, 1985.

[6] “Assessing your weight,” Centers for Disease Control and Prevention, 17-Sep-2020. [Online]. Available: https://www.cdc.gov/healthyweight/assessing/index.html#:~:text=Waist%20Circumference,-How%20To%20Measure&text=Stand%20and%20place%20a%20tape,just%20after%20you%20breathe%20out. [Accessed: 14-Feb-2022].

[7] “Hydrostatic underwater weighing,” DAPA Measurement Toolkit. [Online]. Available: https://dapa-toolkit.mrc.ac.uk/anthropometry/objective-methods/hydrostatic-underwater-weighing. [Accessed: 14-Feb-2022].

[8] W. Siri, “Body Composition From Fluid Spaces And Density: Analysis Of Methods,” Lawrence Berkeley National Laboratory, LBNL Report #: UCRL-3349, 1956, Retrieved from https://escholarship.org/uc/item/6mh9f4nf.

[9] J. Brožek, F. Grande, J. T. Anderson, and A. Keys, “Densitometric analysis of body composition: Revision of some quantitative assumptions*,” Annals of the New York Academy of Sciences, vol. 110, no. 1, pp. 113–140, 2006.

[10] S. Khalil, M. Mohktar, and F. Ibrahim, “The theory and fundamentals of bioimpedance analysis in clinical status monitoring and diagnosis of diseases,” Sensors, vol. 14, no. 6, pp. 10895–10928, Jun. 2014.

[11] P. Li and S. Borle, “Bioelectrical body fat analyzer (ECE 4760: Final Project),” ece.cornell.edu. [Online]. Available: https://people.ece.cornell.edu/land/courses/ece4760/FinalProjects/f2014/smb435_pkl25/webpage/index.html. [Accessed: 07-Feb-2022].

[12] D. S. Alhuwaid, A. Alqahtani, and A. Aloufi , “Bioelectrical Impedance Analyzer,” https://www.pmu.edu.sa/, May-2019. [Online]. Available: https://www.pmu.edu.sa/attachments/academics/pdf/udp/coe/dept/ee/senior%20design%20projects/smart_cleaner_report.pdf. [Accessed: 07-Feb-2022].