This invention discloses a human
fall detection system based on Wi-Fi
channel state information, belonging to the field of
wireless sensing technology. It includes a Wi-Fi
transceiver unit, a data preprocessing unit, a multi-dimensional
feature extraction unit, an adaptive threshold judgment unit, a fall recognition
inference unit, an early warning output unit, and a local storage unit. This invention eliminates the need for users to wear any devices or engage in any
image acquisition, fundamentally eliminating the
poor compliance and strong
foreign body sensation associated with wearable solutions, as well as the privacy leakage risks of visual solutions. This allows the
system to be safely applied in privacy-sensitive scenarios where the elderly frequently engage in activities such as bedrooms and bathrooms. Users can receive 24 / 7 protection without changing their lifestyle. The
system effectively filters out static
multipath interference from walls, furniture, etc., through static environmental baseline subtraction and extracts human spatial posture features using 2D AoA
estimation, accurately distinguishing falls from similar daily actions such as bending over, sitting, and
lying down.