2022-CMEB-Step-N-Count

h1. Algorithms Review

h2. Step counter and status detector

From [1]:

Accelerometer data:

Acceleration along x - axis

Acceleration along y - axis

Acceleration along z – axis

The magnitude of 3-D acceleration data:

Sqr(acc_x^2 + acc_y^2 + acc_z^2)

Get the difference in this magnitude from the previous value.

If the value is greater than a particular threshold value, then increment the steps count.

-Threshold for walking = 17.5

-Threshold for running = 30

p=. !{width:300px}walk-1.png!

h2. Energy Expenditure

"Energy expenditure refers to the amount of energy an individual uses to maintain essential body functions (respiration, circulation, digestion) and as a result of physical activity. Total daily energy expenditure is determined by resting or basal metabolic rate (BMR), food-induced thermogenesis, and energy expended as a result of physical activity[2]."

There are several formulas to calculate a person's energy expenditure, each with a differing level of accuracy and measurement requirements. Our project will focus on the portion of energy expended during physical activity, whether regarding walking, running or even cycling.

In an ideal scenario, either the volume of O2 exhaled or the thermal output of the individual is measured during the physical activity, achieving a highly accurate value of estimated energy expenditure[3]. For our application and for the massively available health monitoring products in the market, this isn't viable, resorting to other metrics such as heart rate, acceleration, body temperature etc.

Given our use of the VitalJacket technology, we will be relying on the individual's self-inputted biometric data, such as weight, height, age, sex and the data acquired by the heart rate sensor and the accelerometer available with the VitalJacket.

To improve the energy expenditure calculation, and considering heart rate is generally a better metric than acceleration[3], several decisions need to be made, such as:

1. Given that the difference in heart rate of someone in a resting rate, when compared to low effort, is so insignificant, should we, for values below a certain HR threshold, solely use the accelerometer or use a REE (resting energy expenditure) value as a placeholder?

2. Due to the lag between our change in acceleration and the correspondent change in heart rate, should we calculate EE using just the acceleration for these sudden differences in speed?

3. If we deem it necessary to offer a TDEE (Total Daily Energy Expenditure) feature in our app, should we consider EPOC[4] (Post-exercise oxygen consumption)?

mariana: 

Kcals/min= 0.001064×Magnitude + 0.087512(Body Mass) - 5.500229 [5]

the Harris-Benedict equation is a commonly used method to estimate energy expenditure based on body mass and gender. However, if you have accelerometer data, you can use this data to more accurately estimate energy expenditure.

Accelerometers are devices that measure acceleration, or the rate of change of velocity over time. By measuring the acceleration of a person's body, it is possible to estimate their energy expenditure by calculating the mechanical work done by their muscles.

There are several methods for using accelerometer data to estimate energy expenditure, and the specific formula used will depend on the type of accelerometer and the equations developed for that specific device. Here are a few examples:

The Freedson equation is a commonly used method that uses a combination of accelerometer data and heart rate data to estimate energy expenditure:

Energy expenditure (kcal/min) = 0.175 x acceleration (g) + 0.029 x heart rate (bpm) - 1.75

The Troiano equation is another method that uses accelerometer data to estimate energy expenditure, based on the assumption that a person's activity level can be classified into one of four categories (sedentary, low, moderate, or vigorous):

Energy expenditure (kcal/day) = (0.1 x acceleration (g) + 2.0) x body mass (kg) x duration (hours/day)

For example, if a person has an acceleration of 1.5 g and a body mass of 75 kg, and they engage in moderate-intensity activity for 2 hours per day, their energy expenditure would be:

Energy expenditure (kcal/day) = (0.1 x 1.5 + 2.0) x 75 x 2

= (0.15 + 2.0) x 75 x 2

= 2.15 x 75 x 2

= 323.5 kcal/day

Again, these are just a few examples of the types of formulas that can be used to estimate energy expenditure from accelerometer data. It is important to note that these methods can have significant error margins, and the accuracy of the estimates will depend on the specific device and the assumptions used in the calculations. It is always a good idea to consult with a healthcare professional or a registered dietitian for personalized nutrition and exercise recommendations.

h2. Distance

References :

1 - programmerworld. (2019) How to create walking step counter App using Accelerometer sensor

and Shared Preference in Android? Available at: [[https://programmerworld.co/android/how-to-create-walking-step-counter-app-using-accelerometer-sensor-and-shared-preference-in-android/]]

2 - Heaney, J. (2013). Energy: Expenditure, Intake, Lack of. In: Gellman, M.D., Turner, J.R. (eds) Encyclopedia of Behavioral Medicine. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1005-9_454

3 - Maughan, Ronald J. (2013). The Encyclopaedia of Sports Medicine (An IOC Medical Commission Publication) || How to Assess the Energy Costs of Exercise and Sport. , 10.1002/9781118692318(), 59–71. doi:10.1002/9781118692318.ch4

4 - https://www.runnersworld.com/training/a22024491/what-is-epoc/

5 - ActiGraph (2018), What is the difference among the Energy Expenditure Algorithms? Available

at: https://actigraphcorp.my.site.com/support/s/article/What-is-the-difference-among-theEnergy-Expenditure-Algorithms (Accessed: 7 November 2022).