Fall Detection

Accelerometer-Based Detection

Signal Features

import numpy as np

class FallDetector:
    def __init__(self, threshold=2.5, window_size=50):
        self.threshold = threshold
        self.window_size = window_size

    def detect_fall(self, accelerometer_data):
        maf = np.sqrt(np.sum(accelerometer_data ** 2, axis=1))
        window_var = np.array([np.var(maf[i:i+self.window_size])
                              for i in range(0, len(maf)-self.window_size)])
        return np.where(window_var > self.threshold)[0]

    def classify_activity(self, features):
        if features['magnitude_var'] > 3.0:
            return 'fall'
        elif features['magnitude_mean'] > 1.5:
            return 'walking'
        return 'stationary'

Prediction Algorithms

Pre-Fall Detection

Feature Set

Alert Systems

Alert Priority

Response Protocol

1. Immediate: Automated emergency call
2. Delayed: Caregiver notification
3. False positive: Learning update