
    In a healthcare monitoring system for elderly patients, develop a function that analyzes n time segments throughout the day and calculates the total number of possible activity pattern combinations during high-risk periods (represented by even-indexed time segments). The calculation should use binomial coefficients to determine these combinations, focusing specifically on the sum of coefficients at even indices, which correspond to peak activity hours when fall risks are elevated.
    

    
import math

def even_binomial_Coeff_Sum(n):
    """
    In a healthcare monitoring system for elderly patients, develop a function that analyzes n time segments throughout the day and calculates the total number of possible activity pattern combinations during high-risk periods (represented by even-indexed time segments). The calculation should use binomial coefficients to determine these combinations, focusing specifically on the sum of coefficients at even indices, which correspond to peak activity hours when fall risks are elevated.
    

    """
import math

def even_binomial_Coeff_Sum(n):
    """
    In a healthcare monitoring system for elderly patients, develop a function that analyzes n time segments throughout the day and calculates the total number of possible activity pattern combinations during high-risk periods (represented by even-indexed time segments). The calculation should use binomial coefficients to determine these combinations, focusing specifically on the sum of coefficients at even indices, which correspond to peak activity hours when fall risks are elevated.
    

    """
    return 1 << n - 1