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Dynamic Swing Plane

We are designing and building a golf tuition system using sensors. There is to be an app on the phone that will receive the signals from the sensors that in turn through the appropriate algorithms will be transformed into useful information for the golfer to create a self-help tool to assist their golf swings. The sensors each contain an accelerometer and gyroscope that are worn on the glove, waist and spine.

We already have orientation data (pitch yaw and roll) in our system which is a transformation of the raw accelerometer and gyroscope data. We want to translate the orientation data to swing plane calculation we can more easily make the link to golf fundamentals to diagnose the swing more effectively.

Step 1 – Transforming the orientation

Using the existing company data, a calculation is made to transform the orientation at each point in the swing to a point on the X, Y and Z axis. From here we will refer to the output of Step 1 as orientation plane.

Step 2 – Interpretation of the orientation plane

The ideal golf swing rotates around a certain plane. Golfers when they move outside this plane either have a bad result or have to make a correction somewhere else in their swing which leads to inconsistent results. We therefore want to measure the outcome of Step 1 against a perfect plane to evaluate where and by how much the actual swing plane diverges. People have different starting orientation in their spine and waist, for this exercise of swing plane we wish to take this effect out by devising a perfect swing plane comparison for that starting point. The other factor we wish to remove as this will be handled separately is any lateral movement in the device eg if the spine has a lateral shift to the right we don’t want to disrupt the swing plane.

One suggestion or possible approach is to transform the swing plane into an equation and measure the variation to that equation. Note: this is an idea, we are open to different methods the Contractor sees fit to measure the efficiency of the swing plane.

Ultimately the output of this Step (2) will feed our diagnosis matrix to provide guidance on prioritized actions to the golfer to improve their swing.

Step 3 – Assistance to transform the method to C sharp

As our application is in C sharp programming language we need to transform the method employed in Step 1 and Step 2 into C sharp so the method can be applied to each golf swing in our system.

Квалификация: 3D-анимация, 3D-рендеринг, Blender, Data Integration, Python

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О работодателе:
( 5 отзыв(-а, -ов) ) shanghai, China

ID проекта: #19761440

12 фрилансеров(-а) в среднем готовы выполнить эту работу за $4217

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