Predicting Subjective Responses From Human Motion: Application to Vehicle Ingress Assessment

Abstract

The ease of entering a car is one of the important ergonomic factors that car manufacturers consider during the process of car design. This has motivated many researchers to investigate factors that affect discomfort during ingress. The patterns of motion during ingress may be related to discomfort, but the analysis of motion is challenging. In this paper, a modeling framework is proposed to use the motions of body landmarks to predict subjectively reported discomfort during ingress. Foot trajectories are used to identify a set of trials with a consistent right-leg-first strategy. The trajectories from 20 landmarks on the limbs and torso are parameterized using B-spline basis functions. Two group selection methods, group non-negative garrote (GNNG) and stepwise group selection (SGS), are used to filter and identify the trajectories that are important for prediction. Finally, a classification and prediction model is built using support vector machine (SVM). The performance of the proposed framework is then evaluated against simpler, more common prediction models.

A systematic review and evaluation of statistical methods for group variable selection

“…The penalty-based methods belong to different frameworks, depending on how they introduce the bi-level sparsity. Breheny and Huang 15 introduced a hierarchical approach, where an outer penalty function is applied to the sum of an inner penalty function as given in formula (7).…”

“…One such situation is the analysis of variables that are interrelated based on correlations or contextual similarities, since ignoring such group structure reduces the stability, consistency, and interpretability of the selection 3 . Methods accounting for group structures have been investigated since at least 1999 4 and have been used in a broad range of applications, including media classification, 5 disease prediction, 6 automotive engineering, 7 voting behavior analysis, 8 emotion recognition, 9 and credit risk analysis 10 . One of the most common applications is in omics research, such as gene expression microarray or single nucleotide polymorphism data 11‐15 .…”

Analysis of human motion variation patterns using UMPCA

“…Participants were asked to enter and exit the vehicle mockup as they would a vehicle. The right-leg-first strategy was used to define the start/end points for ingress trial (Chateauroux 2009, Masoud et al 2016. After completing an ingress/egress trial, participants were asked to rate the ease of getting in and out the vehicle.…”

“…For example, Kay et al (2000) discussed the impact of postoperative gait analysis on the assessment of treatment outcomes and planning on-going care. In the automotive industry, Masoud et al (2016) presented a systematic framework for using human ingress motion trajectories to predict customers' ingress discomfort ratings for improving vehicle design. Although these applications may have different objectives in terms of the usage of motion data, some common questions are often encountered during data analysis.…”