The problem of fitness score is personality driven problem which means the fitness score must be personalized for the individual. Therefore, we spam bytes have solved this problem using recurrent learning . Once we initialized some waits on the scientific data which is general to all individuals then as per the upcoming reading and feedback by the user these weights are adjusted to make these health parameters as personalized one . It uses the Recurrent Neural Network.
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Data collection of 1 person a month
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Data cleaning/preprocessing
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For each factor, calculate differenece between current value and safe value
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If greater than normal, feedback questions are triggered (a) User is facing issues then values are retained (b) User is normal then Values are changes such that error is minimized After this error is calculated.
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If less than normal then error is calculated
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Total deviation is calculated
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FitScore is predicted
- RNN