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Algorithms Review » History » Version 5

Version 4 (Mariana Calado, 21/12/2022 23:24) → Version 5/37 (Mariana Calado, 22/12/2022 00:24)

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

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 are measured during the physical activity, achieving a highly accurate value of estimated energy expenditure[3]. For our application and for the massly 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 accquired 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 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 necessary to offer a TDEE (Total Daily Energy Expenditure) feature in our app, should we consider EPOC[4] (Post exercise oxygen consumption)?

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

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).