Baekhee Lee

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals

An artificial neural network (ANN) model was developed in the present study to classify the level of a drivers cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%).

Directional and spatial motor intentional disorders in patients with right versus left hemisphere strokes.

OBJECTIVE Motor intentional disorders (MIDs) are characterized by dysfunction in the preparation, initiation, maintenance, and termination of goal-oriented actions. In this study, we investigated (1) whether patients with right hemisphere strokes (RHS) and left hemisphere strokes (LHS) differ in the frequency of delayed action initiation (hypokinesia) and motor impersistence; (2) whether there is a directional or hemispatial component of hypokinesia or motor impersistence; (3) whether there is an association between the presence of hemispatial neglect and tests for MID; and (4) the location of injury associated with MID. METHOD Thirty-two patients with acute unilateral stroke (21 with RHS and 11 with LHS) and 12 age-matched healthy controls participated in the study. To determine the presence and severity of directional and spatial hypokinesia and impersistence we used a new apparatus, the Directional Movement Tester (DMT). While being tested with the DMT, the participants held a static bar located either in the right or left hemispace using either their right or left hand and upon stimulus onset pushed the bar either leftward or rightward and maintained a given force for 10 sec. RESULTS AND CONCLUSION The frequency of hypokinesia and impersistence was higher in the RHS group than in the LHS group, but there were no hypokinetic directional or spatial asymmetries. The RHS group did demonstrate left contralesional directional impersistence, but there were no spatial asymmetries of impersistence. Signs of hemispatial neglect were not associated with these measures of MID. Participants with frontal or subcortical lesions were significantly more likely to demonstrate hypokinesia and impersistence than those with posterior lesions.

Development of an Evaluation Method for a Driver’s Cognitive Workload Using ECG Signal

Objective: The present study is to develop an effective evaluation method for a driver’s cognitive workload using electrocardiography (ECG) signal. Background: ECG measures such as heart rate (HR) and heart rate variability (HRV) have been used for cognitive workload evaluation. Since ECG changes by cognitive workload vary largely depending on personal characteristics, an optimal analysis protocol of ECG needs to be tailored to each individual accordingly; however, existing studies have not considered personal characteristics in ECG analysis for cognitive workload evaluation. Method: The proposed evaluation method uses the area under the receiver operating characteristic (ROC) curve (AUC). A preliminary analysis was conducted with ECG data collected in a driving simulator while an n-back task was conducted. AUC analysis was performed for four ECG metrics (mean IBI, SDNN, RMSSD, and RMSE), three window spans (20, 30, and 40 seconds), and three update rates (1, 2, and 3 seconds). Results: It was identified that the optimal ECG analysis parameters of metric, window span, and update rate maximizing the discriminability of cognitive workload evaluation varied between individual drivers. Conclusion: The finding of the present study supports the use of an individually customized ECG analysis protocol for better evaluation accuracy of a drivers’ cognitive workload. Application: The proposed ECG analysis method for cognitive workload evaluation can be applied to development of a safe driving support system.

Development of a Distributed Representative Human Model Generation and Analysis System for Multiple-Size Product Design

The aim of the study is to develop a distributed representative human model (DRHM) generation and analysis system. DRHMs are used for a product with multiple-size categories such as clothing and gloves. It is not easy for a product designer to explore an optimal sizing system by applying various DRHM generation methods because of their complexity and time demands. The existing studies related to DRHM generation protocols and RHM generation methods of three digital human model simulation systems (Jack®, RAMSIS®, and CATIA Human®) were reviewed in the study. The DRHM generation protocol was implemented by providing sophisticated interfaces which offer various statistical and visualization techniques. The system can analyze the multivariate accommodation percentage of a sizing system, provide body sizes of generated DRHMs, and visualize generated DRHMs. The DRHM generation and analysis system can be of great use to efficiently determine an optimal sizing system for a multiple-size product by comparing various sizing system candidates with each other.

Development of HeadForms and an Anthropometric Sizing Analysis System for Head-Related Product Designs:

The present study developed a sizing analysis system based on the Civilian American and European Surface Anthropometry Resource (CAESAR) database of North Americans (n = 2,299) for head-related product designs. To find representative heads from a huge amount of 3D human scan database, a sizing analysis system is required for efficient analysis of sizing systems based on anthropometric measurements. The head of the CAESAR 3D scan were manually edited to improve a quality for better use to the product design. Twenty one anthropometric landmarks were marked on the edited 3D heads to measure 40 anthropometric dimensions related to the head product designs. All head and face dimensions were automatically measured by applying a measurement system coded using Matlab. Fifteen representative headforms were generated in terms of 5 ethnic groups (composite group, Caucasians, American Africans, Asians, and Hispanics) and 3 gender groups (composite gender, males, and females). Finally, the sizing analysis system was developed based on the measurement of the CAESAR for analysis of head and facial measurements and generation of sizing systems.

3D scan to product design: Methods, techniques, and cases

3D scanning technology has derived great opportunities for ergonomic product designs. This paper is aimed to introduce various research cases and methods based on 3D scanning have conducted by an ergonomics laboratory in South Korea. Sizing systems and representative 3D models developed on anthropometric measurements and 3D scan images with technical know-how were applied to the design of various products. Head, face, ear, upper limb, and waist parts, and full body in seated were anthropometrically analyzed for the design of headwear (e.g., helmet, goggle, and headphone), oxygen mask, earphone, arm-wear (e.g., watch, armband), hip protector, and vehicle seat, Customized software for the efficient analyses such as measurement of anthropometric dimensions, analysis of sizing systems, extraction of representative models, and virtual fit evaluation between products and the body were developed and applied in the product design process with massive 3D images. Representative models (e.g., torso and head) were printed in 3D for effective usage to the design and evaluation of related products. Advanced methods and techniques such as finite element modeling, morphing, and skin deformation have been applied to 3D scanned images for an advanced design of product shapes in further researches.

The Effects of Age, Gender, and Hand on Force Control Capabilities of Healthy Adults:

Objective: The present study examined the effects of age (20s to 70s), gender (male and female), and hand (dominant and nondominant) on force control capabilities (FCCs) in four force control phases (initiation, development, maintenance, and termination). Background: Normative data of FCCs by force control phase are needed for various populations in age and gender to identify a type of motor performance reduction and its severity. Method: FCCs of 360 participants (30 for each combination of age group and gender) were measured using a finger dynamometer and quantified in terms of initiation time (IT), development time (DT), maintenance error (ME), and termination time (TT). Results: Although gradual increases (1%~28%) by age were shown in IT, DT, and TT, a dramatic increase in ME was observed among participants in their 50s (26%), 60s (68%), and 70s (160%) compared to those in their 20s~40s. The most distinctive interaction effect of age and gender was found in ME out of the four FCC measures. Lastly, hand and its related interactions were not found significant. Conclusion: Normative FCC data were established for four age groups (20s~40s, 50s, 60s, and 70s) and gender. Application: The normative FCC data can be used for evaluating an individual’s motor performance, screening patients with brain disorders, and designing input devices triggered and/or operated by the finger.

Ergonomic Evaluation of Console Chairs for a Weapon Locating Radar

Objective:The present study is intended to evaluate the usability of a console chair for a weapon locating radar by comparing with different kinds of chair design. Background: Console chairs need to be ergonomically designed to reduce physical workload of operators and improve mission capability; few studies have been reported which systematically evaluate usability of military console chairs. Method: Ergonomic design of a console chair, a bus seat, and an office chair was evaluated in terms of headrest, seatback, seatpan, armrest, and controller on a 7-point scale. Ten males in their 20s and 30s were recruited considering the demographic characteristics of console operators. Results: The satisfaction scores of the console chair for headrest, seatback, and seatpan were significantly higher than those of the bus seat (mean difference [MD] = 0.9) and office chair (MD = 1.3). Meanwhile, the satisfaction scores of the console chair for armrest and controller were significantly lower than those of the office chair (MD = -1.4) and bus seat (MD = -2.2). Conclusion: The armrest and controller of the console chair needs ergonomic improvements for better comfort. Application: The evaluation results of the console chair would be of use for ergonomic console chair design.

A Case Study of Eco-Design for a Small-Size Electric Heater by Performance, Usability, and Life-Cycle Assessments

Life-cycle assessment (LCA) is often employed to quantify the environmental impact of a product in a comprehensive manner. The aspects of performance and usability as well as that of eco-friendliness should be considered in an integrated manner for the market competitiveness of an eco-friendly product. The present study developed a product improvement plan for an eco-friendly electric heater by benchmarking two small-size electric heaters (companies ‘H’ and ‘T’) in terms of performance, usability, and eco-friendliness. The performance measurements such as temperature, humidity, wind speed, noise, and power consumption were collected while the two heaters were operated in a laboratory setting. Then, the usability evaluations such as aesthetics, operation satisfaction, performance satisfaction, and overall satisfaction were surveyed for the two heaters using a 5-point scale (1 for very unsatisfied and 5 for very satisfied). Lastly, the LCA analysis was conducted by following the six-step process of eco-friendly product design provided by KEITI. The analysis results of the two products being integrated with the aspects of product, service, and user, four design improvement directions such as eco-efficient, smart, modularized, and user-support were recommended for an eco-friendly electric heater. These proposed concepts would be useful to develop an eco-friendly electric heater design with a high level of market competitiveness. †

Development of Statistical Geometric Models for a Driver’s Hip and Eye Locations

Drivers’ hip locations (HLs) and eye locations (ELs) have been used as reference data to design an ergonomic automobile interior. Although many prediction models of a driver’s HL and EL have been developed, the developed models have limitations in terms of prediction accuracy and stability. The objectives of the present study are (1) development of statistical geometric models (SGMs) of a driver’s HL and EL, and (2) evaluation of the accuracy of the SGMs. Forty drivers’ preferred driving postures were measured by a motion capture system in 3 different vehicle conditions (coupe, sedan, and SUV). The SGMs were developed by incorporating the geometric relationships between HL, EL, anthropometric dimensions, and driving postures and the statistical relationships between body link lengths and surface landmark lengths. The SGMs were evaluated quantitatively by comparing the Reed et al. (2002)’s models in terms of prediction accuracy. As a result, the average adj. R2 of SGMs is 1.1 ~ 3.7 times higher than Reed et al.’s models and root mean squared error (RMSE) of the SGMs is 1.7 ~ 1.8 times smaller than the Reed et al.’s models. Moreover, RMSE of the SGMs in three vehicle conditions are 1.7 ~ 4.3 times smaller than the Reed et al.’s models. These results indicate that the accuracy of the SGMs are more accurate and stable than the Reed et al.’s models in all three vehicle conditions. The developed SGMs have high applicability to the ergonomic design of automobile interiors such as the seat adjustment range and windshield height.