Human Posture Identification Using a MIMO Array

Abstract

Abstract:The elderly are constantly in danger of falling and injuring themselves without anyone realizing it. A safety-monitoring system based on microwaves can ease these concerns. The authors have proposed safety-monitoring systems that use multiple-input multiple-output (MIMO) radar to localize persons by capturing their biological activities such as respiration. However, our studies to date have focused on localization, which is easier to achieve than an estimation of human postures. This paper proposes a human posture identification scheme based on height and a Doppler radar cross section (RCS) as estimated by a MIMO array. This scheme allows smart home applications to dispense with contact and wearable devices. Experiments demonstrate that this method can identify the supine position (i.e., after a fall) with 100% accuracy, and the average identification rate is 95.0%.

Data Processing and Wearable Systems for Effective Human Monitoring

“…Results suggested that liquid metal sensors can be a valid substitute for the inertial measurement units in capturing specific joint angles and movements. Sasakawa et al [9] presented a system to monitor the human posture identification scheme through an array of MIMO radars. This system is designed to be a safety-monitoring system to aid the elderly in danger of falling.…”

Measurement-Based Feasibility Exploration on Detecting and Localizing Multiple Humans Using MIMO Radio Channel Properties

“…For the same power level, the monostatic radar systems have a much lower spatial range of operation than bistatic radar system [16], hence [14] needed distributed monostatic radars for the human detection purpose. Moreover, the perfect condition combining both the UWB MIMO system and the super-resolution algorithm on multipath extraction in [13] is not always available, [17], [18] demonstrated the localization of human through super-resolution algorithm in bistatic MIMO system without UWB. In [17], [18], the authors have utilized the bistatic MIMO radars and the MUSIC (MUltiple SIgnal Classification) algorithm on multipath extraction to estimate the human direction relative to the antenna locations.…”

“…Moreover, the perfect condition combining both the UWB MIMO system and the super-resolution algorithm on multipath extraction in [13] is not always available, [17], [18] demonstrated the localization of human through super-resolution algorithm in bistatic MIMO system without UWB. In [17], [18], the authors have utilized the bistatic MIMO radars and the MUSIC (MUltiple SIgnal Classification) algorithm on multipath extraction to estimate the human direction relative to the antenna locations. They also utilized the system's Doppler radar cross-section for estimating the posture of a human at dedicated location.…”

A Plug and Play IoT Wi-Fi Smart Home System for Human Monitoring

“…Modern systems exploit human monitoring mainly to improve the energy management of the building [2][3][4][5][6][7]. However, data related to the users and how they live in their own home environment can find straightforward applications in health management, allowing for early detection of behavioral trends and anomalies possibly relevant to one's wellbeing [8][9][10][11][12][13][14].…”

“…It is worth stressing that the aim of this work is not to develop and demonstrate a new behavioral analysis method, but to present a new hardware architecture conceived to collect data usable by behavioral analysis models developed elsewhere [16,[40][41][42]. These tests show the usability and convenience of data collected and demonstrate that it is possible to take advantage of the flexibility of the Wi-Fi platform while eliminating costs given by the need of additional hardware (i.e., home servers and routers, adopted in [13][14][15][16]).…”