Assessing ergonomic risks of software: Development of the SEAT

An earphone fit deviation analysis algorithm

This study provides an accurate method for evaluating the fit of earphones, which could be used for establishing a linkage between interference/gap values with human perception. Seven commercial CAD software tools stood out and were explored for the analysis of the deviation between earphone and ear. However, the current deviation analysis method remains to be improved for earphone fit evaluation due to excessive points in the calculation (Geomagic Wrap and Siemens NX), lack of value on interference (Geomagic Control X), computation boundary required (Rapidform XOR/Redesign), repetitive computation with same points and inclined calculation line segment or even invalid calculation (Solidworks, Creo). Therefore, an accurate deviation analysis algorithm was promoted, which calculated the deviation between earphone and ear exactly and classified the interference set and gap set precisely. There are five main procedures of this algorithm, which are point cloud model pre-processing, the generation of distance vectors, the discrimination of interference set and gap set, the discrimination of validity, and statistical analysis and visualization. Furthermore, the usability and validity of the deviation analysis algorithm were verified through statistical analysis and comparing visual effects based on the earphone-wearing experiment. It is certified that the deviation analysis algorithm is appropriate for earphone fit evaluation and the eight indexes of this algorithm were proved to be related to subjective comfort scores. It is meaningful for ear-worn product fit analysis, design, and development phases.

Is low-cost motion capture with artificial intelligence applicable for human working posture risk assessment during manual material handling? A pilot study

BACKGROUND

Assessing working posture risks is important for occupational safety and health. However, low-cost assessment techniques for human motion injuries in the logistics delivery industry have rarely been reported.

OBJECTIVE

To propose a novel approach for posture risk assessment using low-cost motion capture with artificial intelligence.

METHODS

A Kinect was adopted to obtain red-green-blue (RGB) and depth images of the subject with 24 postures, and the human joints were extracted using artificial intelligence. The images were registered to obtain the actual three-dimensional (3D) human joint angle.

RESULTS

The root mean square error (RMSE) significantly decreased. Finally, two common methods for evaluating human working posture injuries-the Rapid Upper Limb Assessment and Ovako Working Posture Analysis System-were investigated.

CONCLUSIONS

The outputs of the proposed method are consistent with those of the commercial ergonomic evaluation software.

Analysis of the auricles and auricular shape types for ear-related wearables: A study of mainland Chinese sample aged 15–79

BACKGROUND: Comprehension of the complex shape of the auricle and how it differs in terms of factors such as sex, age, and side have become an imperative aspect of the fabrication and service delivery of products that are natural, functional, and healthy for users. OBJECTIVE: This study was aimed at providing a clear understanding of the anthropometric characteristics based on age, sex, size, and side and shape type of the auricles of mainland Chinese samples. METHODS: Casting and 3D scanning were employed to obtain eighteen auricular measurement variables from 1120 subjects (aged 15–79). Examination of sex-related and bilateral differences were conducted. Furthermore, factor analysis was employed to establish the factors associated with the variations in auricular shape. Also, hierarchical cluster analysis was performed to classify the auricular shapes of individuals. RESULTS: The auricular inclination angle, conchal depth and tragal height did not exhibit any specific trend across the age groups. No significant bilateral difference was observed in both genders. The auricular shapes were classified into five types according to six major factors. CONCLUSIONS: It was observed that measurement variables of the Chinese auricles changed continuously with age, with most of the linear variables exhibiting a steady increase. The apparent strong association between the auricular types and age groups indicate that a person’s auricular shape may change with age.

A study on segmentation and refinement of key human body parts by integrating manual measurements

Optimal ergonomic design for consumer goods (such as garments and furniture) cannot be perfectly realised because of imprecise interactions between products and human models. In this paper, we propose a new body classification method that integrates human skeleton features, expert experience, manual measurement methods, and statistical analysis (principal component analysis and K-means clustering). Taking the upper body of young males as an example, the proposed method enables the classification of upper bodies into a number of levels at three key body segments (the arm root [seven levels], the shoulder [five levels], and the torso [below the shoulder, eight levels]). From several experiments, we found that the proposed method can lead to more accurate results than the classical classification methods based on three-dimensional (3 D) human model and can provide semantic knowledge of human body shapes. This includes interpretations of the classification results at these three body segments and key feature point positions, as determined by skeleton features and expert experience. Quantitative analysis also demonstrates that the reconstruction errors satisfy the requirements of garment design and production. Practitioner summary The acquisition and classification of anthropometric data constitute the basis of ergonomic design. This paper presents a new method for body classification that leads to more accurate results than classical classification methods (which are based on human body models). We also provide semantic knowledge about the shape of human body. The proposed method can also be extended to 3 D body modelling and to the design of other consumer products, such as furniture, seats, and cars. Abbreviations: PCA: principal component analysis; KMO: Kaiser-Meyer-Olkin; ANOVA: analysis of variance; 3D: three-dimensional; 2D: two-dimensional; ISO: International Standardisation Organisation; BFB: body-feature-based.