# Resistance Temperature Detector Calibration for Sweat Sensors

Glucose and Lactate are two analytes in sweat that would be highly desirable to apply sweat sensing technology to, each for their own individual reasons. Since the biosensing technology typically used to detect these analytes utilizes enzymatic reactions, temperature of the sample being tested must be taken into consideration when interpreting results due to its effects on enzymatic activity. Therefore, temperature sensors are an essential component of any sweat sensor that aims to give reliable feedback on either/both of these analytes. Multiple temperature sensing technologies exist, but a simple, commonly used technology is resistance temperature detectors (RTDs). These simple circuits use a Wheatstone bridge with a pure metal resistor that is exposed to the sample being tested. That resistor has a temperature-dependent resistance, and its resistance affects the voltage output of the Wheatstone bridge. In order to calibrate your sensor (a necessary process to ensure it gives accurate results), you must be able to use voltage outputs of known temperatures to identify the relationship between voltage and temperature. This problem will help us learn to do so.

Problem Statement

The Wheatstone bridge shown below (figure 2.) has four resistors, three of equal resistance R=10Ω and one temperature-varying platinum resistor RT. A voltage VE=1V is provided to the system by a battery as shown. Vo is defined as the voltage difference between points a and b, and is given by the general Wheatstone bridge equation provided below (figure 1.). Resistance RT is given by RT = R0(1+α(T-T0), where α is the temperature coefficient of platinum, α= 0.00385/°C. Given that R0= 10Ω and T0=0°C…

a. Write an equation for Vo in terms of T

b. Find Vo at T=20°C, T=30°C, and T=40°C

c. Devices aren’t always exact. Your RTD is giving values of Vo(20)=19.0mV, Vo(30)=28.3mV, and Vo(40)=37.2mV. Plot these values and find a line of best fit for your RTD (assuming linear relationship*)

d. Find the voltage Vo that would be expected at T=37°C

Figure 1. Wheatstone bridge equation

Figure 2. RTD setup

*Assumptions:

• Linear relationship between Vo and T- RTDs display much more linear behavior than thermocouples. They are not exactly linear, but for the purposes of this problem and learning how to calibrate, it is a fair assumption. It will cause the most error in the middle of our range of estimation, due to the parabolic nonlinearity of the true relationship between Vo and T. [1]

Solution

Figure 3. The written solutions for a, b, and d

Figure 4. Plot for part c

The algebra for solutions to parts a, b, and d of the problem are provided in figure 3. The plot for part c, created in Excel, is provided in figure 4. This plot was created by creating a column of temperature data and a column of the corresponding voltage data given in the problem statement for part c, highlighting those two columns, and creating a scatter plot. A line of best fit was added to the plot, and the equation for the line was displayed on the graph itself. Excel makes linear approximations for data sets like these very easy. While the linear approximation may not be the best fit for our data set, it appears to be very accurate, with an Rvalue of 0.9998. Our final answer for Vo at 37°C makes sense, given that 34.45mV is between the values for 30°C and 40°C, 28.3mV  and 37.2mV, respectively, and closer to that of 40°C. The linear approximation we made is a limitation of this solution. For a sweat sensing technology that gives medically relevant feedback to the user, we would want our analyte sensing results to be as accurate as possible, which would involve a curve-fitting technique as opposed to a linear approximation for our RTD. With the linear calibration we performed, we could use the values of Vo received from our RTD to determine the temperature of samples between 20-40°C with a pretty high level of accuracy.

References

[1] Trump, B. (2011). Analog linearization of resistance temperature detectors. Retrieved from http://www.ti.com/analog-circuit/aaj-article.html

# Delayed Onset Muscle Soreness: What We Know and What We Don’t (Emphasis on Don’t)

Ever get that feeling two days after a tough run, or a ride that you knew was just a few miles too long, or your first leg day in months (come on, we’re all guilty of that), where you begin to question whether you will ever walk the same again? Walking down the stairs feels like torture, and your quads feel like they get angrier at you with every step you take? Muscle soreness, more specifically delayed onset muscle soreness (DOMS) is common in athletes of all levels of expertise. It occurs after performing a training activity that is unfamiliar. This could be activities than an athlete has not performed in a few months, activities they’ve never performed before, or even simply an intensity level or duration of exercise that they don’t normally reach, despite performing that exercise regularly. These unfamiliar activities, also known as eccentric training, are known to induce severe muscle soreness characterized by increasing intensity of symptoms beginning as late as 24-48 hours after exercise and lasting for days. The underlying physiological mechanism causing DOMS is still unknown and highly disputed, but at least six hypothesized theories for this mechanism have been proposed: lactic acid, muscle spasm, connective tissue damage, muscle damage, inflammation, and enzyme efflux theories [1]. Currently, there exist therapies that have been experimentally shown to decrease DOMS prevalence, including various hydrotherapies [2] and foam rolling [3], but more effective preventative therapies could probably be developed if the underlying physiological mechanism was identified. In order to better understand this phenomenon and the unfortunate encounters I’m sure we’ve all had with it, we are going to look into some of those proposed mechanisms and try to get some insight on how it works (or doesn’t).

Lactic acid is easy to blame for exercise-related muscle pain because of its high production rates during exercise and its perceived role in muscle fatigue and soreness (which is often highly exaggerated). While lactic acid is a common byproduct of exercise, its role in the development of DOMS is likely insignificant. A study performed in 1983 measuring blood lactic acid concentration before and during two different 45-minute treadmill exercises, one on a level surface and one at a 10% decline, found that DOMS was not prevalent in level-surface runners, even though lactic acid concentration was significantly increased. Conversely, downhill runners saw no significant increases in lactic acid concentrations but experienced significant DOMS [4]. There was clearly no relationship between presence of lactic acid and development of DOMS, and the two in fact appeared to be mutually exclusive, so let’s move on to another of the previously mentioned theories.

The inflammation theory initially seems to have a bit more validity, as the similarities between the acute inflammation response, a response to various types of injury including muscle damage, and DOMS are striking. Both phenomena can be characterized by pain, swelling, and loss of function at the area of interest. The time lines seem to match up as well, as both have been reported to increase in severity for about 48 hours and show signs of healing at 72 hours. The issue with this theory though, is the lack of physiological evidence, which is arguably the most important kind. Studies investigating the relationship between DOMS onset and inflammatory biomarkers, like white blood cells and neutrophils, have often failed to find significant results, leading us to believe that inflammation does not cause DOMS [5]. Another drawback of the inflammation theory is the ineffectiveness of anti-inflammatory drugs in preventing DOMS-related pain. A study done using an anti-inflammatory drug and placebo on athletes undergoing eccentric bicycle exercise found no changes in subjective soreness between drug and placebo groups, suggesting that inflammation is not the source of DOMS pain [6]. We won’t completely remove inflammation from the picture though, as it may play more of a role than it appears.

While inflammation itself is likely not the cause of DOMS pain, inflammatory-related processes may not be completely innocent. Bradykinin, an inflammatory mediator, is believed to play a role in DOMS after a study done in 2010 by Murase et al [7]. This study used a previously established rat model of DOMS to show that injecting a B2 (but not B1) bradykinin receptor antagonist 30 minutes before exercise completely prevented DOMS in those rats. The antagonistic effects of the drug used, HOE 140, only last about an hour in the body, and they found that when injecting it 30 minutes after exercise, it had no effect in preventing DOMS. The results can be seen below.

This suggests that bradykinin released during exercise plays a direct role in the development of DOMS, and that preventing that bradykinin from interacting with the B2 receptor prevents DOMS. The role of bradykinin and the B2 receptor in the development of DOMS is not well understood, but it seems like a step in the right direction to me.

There is too much research out there on DOMS to cover in one lowly blog post. I wanted to debunk the lactic acid theory as lactic acid is often a scapegoat for exercise-related pain that is likely sourced elsewhere. While inflammation and DOMS have many similarities that may lead some to believe that there is a causal relationship there, that is also likely not the case. However, there is definitely evidence of some sort of relationship between the two. Further research into the physiological pathway that leads to DOMS is definitely needed to make any conclusive statements on the issue, and the bradykinin B2 receptor pathway is probably a good place to start. But until then, you’re just going to have to suck it up next time you feel like your quads will never work again two days after your new leg routine. Many have been there and survived before. You will too.

Questions to consider:

What distinguishes DOMS from standard muscle soreness?

Think about any times you may have experienced DOMS- what were you doing and why do you think it led to DOMS?

How could you determine the presence of DOMS in animal models when it cannot be subjectively reported? (Hint: check reference 7 for ideas)

How could preventative therapies for DOMS promote better health and wellness?

References:

[1] Cheung, K., Hume, P. A., & Maxwell, L. (February 01, 2003). Delayed Onset Muscle Soreness: Treatment Strategies and Performance Factors. Sports Medicine, 33, 2, 145-164.

[2] Vaile, J., Halson, S., Gill, N., & Dawson, B. (March 01, 2008). Effect of hydrotherapy on the signs and symptoms of delayed onset muscle soreness. European Journal of Applied Physiology, 102, 4, 447-455.

[3] Pearcey, G. E., Bradbury-Squires, D. J., Kawamoto, J. E., Drinkwater, E. J., Behm, D. G., & Button, D. C. (January 01, 2015). Foam rolling for delayed-onset muscle soreness and recovery of dynamic performance measures. Journal of Athletic Training, 50, 1, 5-13.

[4] Schwane, J. A., Watrous, B. G., Johnson, S. R., & Armstrong, R. B. (January 01, 1983). Is Lactic Acid Related to Delayed-Onset Muscle Soreness?. The Physician and Sportsmedicine, 11, 3, 124-31.

[5] Smith, L. L. (January 01, 1991). Acute inflammation: the underlying mechanism in delayed onset muscle soreness?. Medicine and Science in Sports and Exercise, 23, 5, 542-51.

[6] Kuipers, H., Keizer, H. A., Verstappen, F. T., & Costill, D. L. (January 01, 1985). Influence of a prostaglandin-inhibiting drug on muscle soreness after eccentric work. International Journal of Sports Medicine, 6, 6, 336-9.

[7] Murase, S., Terazawa, E., Queme, F., Ota, H., Matsuda, T., Hirate, K., Kozaki, Y., … Mizumura, K. (January 01, 2010). Bradykinin and nerve growth factor play pivotal roles in muscular mechanical hyperalgesia after exercise (delayed-onset muscle soreness). The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 30, 10, 3752-61.

# Tired of Blood Tests? Don’t Sweat it! (Or do, I Suppose)

I think I stand with the majority of the population when I say that I do not like needles. Blood work, as I’m sure you can imagine, is not really my cup of tea. As I sit there in that dreadfully uninviting chair with a rubber tourniquet tied way-too-tightly-for-comfort around my upper arm, I find myself wishing there was a less invasive alternative, ideally one that doesn’t leave me with a puncture wound. Well, luckily for me and any other sane individual who shares my distaste for needles, the future looks bright. Sweat has historically been overlooked as a biosensing platform despite carrying many of the same biomarkers, chemicals, and solutes that are carried in blood. This stems from a variety of different complications associated with sweat sensing that simply don’t exist for blood tests, and these complications have been enough to prevent any significant progress in the field for a long time. It was not until a group of scientists from the University of Cincinnati were issued an intriguing patent on January 22nd of this year that the field of sweat sensing technology began to see hope.

Now all of that is a bit dramatic, but let’s be real. How many of you would have kept reading if I started off with “Devices for integrated, repeated, prolonged, and/or reliable sweat stimulation and biosensing” (the official name for the patent in question)? I’m sure sweat stimulation isn’t something you planned on spending a great deal of time thinking about today, but you’re here now and boy let me tell you, this is exciting stuff. US patent number 10182795 could have some major implications in the near future across multiple facets of life. Inventors Jason Heikenfeld and Zachary Cole, working out of the assignee of the patent, the University of Cincinnati, have put forth some novel approaches to addressing the complications associated with sweat biosensing, specifically the inability to consistently gather enough sweat from one area for testing, skin irritation, and the contamination of sweat samples from chemicals used to stimulate sweating, like pilocarpine. Their patent, filed on October 17, 2014 and classified under CPC A61B 5/1491 (using means for promoting sweat production), among other classifications, describes a medical technology that has potential for a wide-ranging impact, and the many claims they make (13 to be exact) sound promising.

So let’s talk about the invention. At its core, it’s a method of sweat stimulation and sampling through device-skin interface that could be deployed through a variety of different mediums, including patches, bands, straps, clothing, wearables, etc. Utilizing multiple sweat stimulation pads controlled by a timing circuit capable of selectively activating/deactivating individual pads, this technology is able to rotate through the pads over time. This prevents skin irritation caused by the single-pad, continuous sweat stimulation that has been used in this design’s predecessors, and also allows more consistent sweat collection due to the rotation between fresh sweat stores. One commonality between this design and previous sweat sensors is the method of sweat stimulation, but even within that apparent commonality there are improvements that have been made. While this design still plans to use a molecular method of drawing sweat out of the skin, like pilocarpine, it also includes a filtration component, or membrane, to ensure purity of the sweat sample collected. Once collected, the sample is pumped to a sensor by a microfluidic component to analyze the concentration of the analyte of interest for that sensor. The design can be seen in better detail below.

The inventors claim that this device will collect and analyze sweat over extended periods of time through the components and methods described above. If that is in fact true, this technology could soon be in use everywhere. From athletes seeking to maximize their body’s performance to nurses caring for neonates to patients undergoing pharmacological monitoring, this technology could be a real breakthrough in systemic biomarker detection. Why bother with a needle when you can get the same information by slapping a patch on your arm? This patent has the potential to render most blood tests for analytes present in sweat obsolete. There is likely still a long road ahead before it reaches the market, and it may very well end up like the vast majority of US patents that never make it there. But I know I’ll be on the lookout for clinical trials over the next 5-10 years. I hope you will too.

Reference

Heikenfeld, Jason C., Sonner, Zachary Cole. (2019). United States Patent No. 10182795B2. Retrieved from http://pdfpiw.uspto.gov/.piw?PageNum=0&docid=10182795&IDKey=263AB8D65766%0D%0A&HomeUrl=http%3A%2F%2Fpatft.uspto.gov%2Fnetacgi%2Fnph-Parser%3FSect1%3DPTO2%2526Sect2%3DHITOFF%2526p%3D1%2526u%3D%25252Fnetahtml%25252FPTO%25252Fsearch-bool.html%2526r%3D3%2526f%3DG%2526l%3D50%2526co1%3DAND%2526d%3DPTXT%2526s1%3Deccrine%2526s2%3Dsensor%2526OS%3Deccrine%252BAND%252Bsensor%2526RS%3Deccrine%252BAND%252Bsensor