Fatigue level detection using multivariate autoregressive exogenous nonlinear modeling based on driver body pressure distribution

Prolonged driving causes symptoms of fatigue in drivers and changes their physical condition during driving. The purpose of this paper is to use a force measurement system located in the driver’s seat by force-sensitive resistance pressure sensors in order to record the received information to predict fatigue by learning regression-based models. This system is designed with 16 FSR (Force Sensing Resistor) sensors mounted on the seat and its backrest that records the driver’s body’s data, based on the force exerted by the driver on the seat in standard mode and during driving at various times. Fatigue level prediction is based on the trained nonlinear autoregressive exogenous model. In this procedure, models based on multivariate regression are first trained, and then correctness is checked. In this paper, the fatigue index is divided into five parts from 0 to 100 included fully conscious, slightly tired, moderately tired, very tired, and extremely tired, so the criterion for diagnosis is crossing the 75% of fatigue index and entering the extremely tired range. The results show that nonlinear models based on exogenous autoregressive have better performance than the linear mode, and even in the nonlinear model of NARX neural network, the fatigue of one step ahead is well predictable. A flopped state will be predictable when the body is immersed in the seat due to fatigue, so is far from the standard sitting position and will be in the extremely tired warning range.

Pillow Support Model with Partitioned Matching Based on Body Pressure Distribution Matrix

(1) Objective: Sleep problems have become one of the current serious public health issues. The purpose of this research was to construct an ideal pressure distribution model for head and neck support through research on the partitioned support surface of a pillow in order to guide the development of ergonomic pillows. (2) Methods: Seven typical memory foam pillows were selected as samples, and six subjects were recruited to carry out a body pressure distribution experiment. The average value of the first 10% of the samples in the comfort evaluation was calculated to obtain the relative ideal body pressure distribution matrix. Fuzzy clustering was performed on the ideal matrix to obtain the support surface partition. The ideal body pressure index of each partition was calculated, and a hierarchical analysis of each partition was then performed to determine the pressure sensitivity weight of each partition. Using these approaches, the key ergonomic node coordinates of the partitions of four different groups of people were extracted. The ergonomic node coordinates and the physical characteristics of the material were used to design a pillow prototype. Five subjects were recruited for each of the four groups to repeat the body pressure distribution experiment to evaluate the pillow prototype. (3) Results: An ideal support model with seven partitions, including three partitions in the supine position and four partitions in the lateral position, was constructed. The ideal body pressure distribution matrix and ideal body pressure indicators and pressure sensitivity weights for each partition were provided. The pillow that was designed and manufactured based on this model reproduced the ideal pressure distribution matrix evaluated by various groups of people. (4) Conclusion: The seven-partition ideal support model can effectively describe the head and neck support requirements of supine and lateral positions, which can provide strong support for the development of related products.

Adaptive Automobile Seat Design Based on Ergonomic Principle

In order to improve the comfort of automobile seat, it is necessary to analyse and study the design method of automobile seat. A design method of adaptive automobile seat based on ergonomics principle is proposed. The height, width, depth, backrest, seat inclination and backrest inclination of automobile seat as well as the sitting posture physiology and body pressure distribution of human body are analysed. The frame of automobile seat is designed by using aluminium alloy in PROE software, the size of the energy absorption of headrest, cushion and seat are determined according to national regulations. By analyzing the back force, pillow force, seat belt force and seat belt locking, the force of automobile seat, the strength of back, head pillow and seat cushion of automobile seat are designed and the design of adaptive automobile seat is completed. The experimental results show that the proposed method has high comfort, low processing cost and high production efficiency.