Multi-Modal Ergonomic Evaluation of High-Speed Rail Seating by Integrating Electromyography, Skin Conductance Response, and Scenario-Based Analysis

Summary

The research evaluates physiological and ergonomic differences among high-speed rail seating classes by integrating electromyography, skin conductance response, and scenario-based analysis to quantify muscle fatigue, stress responses, and overall comfort under realistic travel activities.

Abstract

Most existing studies on high-speed rail (HSR) seating comfort are based on subjective surveys and pressure maps; there is no physiological reporting on muscle fatigue and stress accrual with longer travel periods. The assessment of dynamic sitting performance in different travel conditions is rather difficult due to the impossibility of the traditional laboratory-based investigations to reproduce real-life posture variations. To surmount these limitations, the present research compares business, first-class, and economy-class seats in a real-world HSR travelling scenario through the application of multi-modal ergonomic testing, which involves the use of electromyography (EMG), skin conductance response (SCR), and scenario-based behavioral testing. The 30 participants were divided into two seating classes and placed in four functional situations: entertaining, dining, working, and resting. Whereas SCR was used to monitor autonomic stress responses, EMG was used to record muscular activity in the shoulders, lumbar, and neck. The results indicate that although business-class chairs reduce lumbar strain, they do not eliminate the weariness of upper limbs and necks, especially in the reclining position. The first-class seats are maximum in terms of working postures, but they cannot offer flexible support for varied body proportions, which results in head and lumbar discomfort. Owing to their low level of adjustability, economy-class seats produce the largest amount of muscular tension, despite their high level of lumbar and neck support. This research provides an understanding of adjustable, ergonomically idealized seating for trains in future models and the significance of incorporating behavioral and physiological information into dynamic seat analysis.

Introduction

Global mobility has been transformed by the quick development of high-speed rail (HSR) networks, which shorten travel times and improve accessibility. Even as HSR infrastructure has undergone constant technical improvements, seating comfort, especially during extended travel, remains a crucial yet understudied component of the passenger experience. According to earlier studies, badly made seats can lead to chronic musculoskeletal strain, discomfort, and muscular fatigue^1,2,3. These problems are made worse in lower-tier seating classes, where cost-driven design trade-offs frequently result in inflexible, non-adjustable constructions that are unable to take into account a variety of body shapes and postural requirements. International train systems, like France's TGV and Japan's Shinkansen, have incorporated ergonomic principles to improve seating designs, but there is still a dearth of systematic, empirical research on HSR seating comfort, especially about physiological muscle stress⁴. A deeper understanding of passenger comfort and tiredness accumulation can be obtained by implementing human factors approaches⁵. Creating a reliable evaluation system that measures biomechanical strain while taking contextual seat usage and real-world passenger behaviors into account is the main problem.

Recent research in ergonomics and human factors has demonstrated that EMG and SCR could provide objective real-time information on physiological responses associated with muscle fatigue and seated pain⁶. EMG is a widespread technique of evaluating localized strain of muscles during sitting postures and is an electrical measure of muscle activity. Moreover, SCR produces autonomic nervous system responses, which provide an indirect measure of physical discomfort and stress, particularly in prolonged static poses that are static⁷. These methods give a more detailed understanding of ergonomic weaknesses in the design of the seats by measuring voluntary and involuntary physiological reactions. It is worth noting that previous studies have successfully applied EMG and SCR to research task performance in high-cognitively challenging settings and digital interaction systems to demonstrate their versatility in a human-centered design evaluation. However, they are yet to be directly applied in research on seating of rail transportation, and further exploration of their potential as an instrument to determine passenger comfort levels in dynamic multi-scenario settings is necessary⁸.

The absence of scenario-based distinction in data collection is a significant drawback of current ergonomic assessments of HSR seating. Conventional seat comfort research frequently uses static lab environments that do not accurately reflect real-world travel circumstances². But in a real-world HSR setting, passengers do a range of tasks like eating, working, relaxing, and entertaining themselves, all of which need different muscular load patterns and postural adjustments⁹. Researchers can identify biomechanical stressors unique to each usage context by combining EMG and SCR within a scenario-based framework. This enables a more accurate assessment of seat performance across various travel behaviors. Although this method has proven successful in domains like digital ergonomics and human-machine interaction, its application to transportation seating design is still in its infancy¹⁰. Furthermore, only a few studies have used multi-modal physiological and behavioral measurements to systematically compare muscle fatigue across various seating classes, even though few have investigated pressure distribution mapping¹¹.

The conceptual framework used here (Figure 1) shows that the development of high-speed rail, the experience of passengers, and urban agglomeration are interconnected in a complex manner. It is worth noting that this highlights how changing the lifestyle of passengers and city development pose new requirements for the design of HSR seats, with attention to human-machine interaction, travel behavior, and passenger comfort as the primary considerations. The HSR travel needs are also affected by the connectivity existing between the metropolitan clusters that determine the expectations of passengers as to long-term comfort and the ergonomic nature of the seats. The design of the traditional seats is also being challenged by the changing work patterns, lifestyle changes, including the more frequent use of mobile devices, and the changing work habits of people that require innovative ergonomic design. The results justify a more plastic, humanized way of designing seats, and this is in line with the objectives of the research.

Figure 1: Intercity high-speed rail research conceptual framework. The correlation between population, urban agglomeration, and high-speed rail (HSR) research is illustrated here. It focuses on the effect of urban growth and modern living on passenger transit patterns, consumption demand, and space requirements. Additionally, the diagram highlights the human-centered approach that links the processes of urbanization, mobility, and lifestyle changes by illustrating how HSR influences and responds to urban clusters and shifting passenger behaviors. Please click here to view a larger version of this figure.

To fill these gaps, this paper has methodically compared the physiological effects of various HSR seating arrangements in the business, first, and economy classes using EMG and SCR. The original feature of this research is the transitional nature of the scenario-based experimental design that makes it possible to discover the issues of muscular fatigue patterns peculiar to the various work, rest, dining, and entertainment postures. The research offers quantitative physiological information and involves actual passenger behavior to effectively give an ergonomic and human factors solution to the seating analysis.

The study provides evidence-based suggestions on lumbar adaptability, optimization of armrest table positions, and sit structures depending on cross-sectional variations in muscle loads and autonomic response reactions to various types of seats. In addition to providing new science on the ergonomics of long-term sitting in HSR, the current research also defines feasible design thinking about the future versions of HSR seats in cases where the emphasis of the passengers is on comfort, inclusivity, and flexibility. The research advances the old debate of ergonomic seating in transportation and offers guidance to high-speed train manufacturers on how to accommodate various passenger requirements in their seating category using the integration of biomechanical and real-life human practices.

Protocol

Ethical approval was obtained from the Tsinghua University Science and Technology Ethics Committee Medical Subcommittee (Approval No.: THU01-20250087), and all participants provided written informed consent before joining the study.

The research determines physiological strain and muscle fatigue in the different high-speed rail (HSR) seating classes through a multi-modal ergonomic evaluation. This approach gives a more dynamic consideration compared to the traditional static measurements of muscular activity and physiological stress under diverse seating positions and traveling events through the combination of EMG and SCR in the framework of a scenario simulation. To measure the intensity of muscle activation and the progression of tiredness, two physiological evaluation metrics that are commonly used in ergonomic and biomechanical evaluations, such as median frequency (MF) and root mean square (RMS), were also included¹².

The research used comparable experimental controls and a neutral baseline (pre-test calibration). As a neutral physiological reference for normalization, participants recorded their resting EMG and SCR levels during a 10 min baseline calibration in a standard upright position before each session. Furthermore, business-, first-, and economy-class seat comparisons served as experimental controls, enabling the separation of seat-specific effects under the same scenario-based activities.

Experimental environment and equipment
For ecological validity, all measurements were done in actual high-speed rail (HSR) cabins. Figure 2 depicts the seating and environment of the business-class section, the ergonomic solutions, the cabin lighting, and the passenger seating solutions. These elements contribute to the general level of comfort and, in addition, influence such physiological reactions as SCR changes and EMG activity. The wearable sensor system in this research, described in Figure 3, was used in physiological monitoring. The apparatus used in the experiment consisted of:
Electromyography (EMG): Surface EMG sensors were attached to the lower back, neck, and shoulders to record muscular activity amplitude (µV) and median frequency changes (Hz), which are indicators of muscle fatigue.
Skin conductance response (SCR): A Shimmer3 GSR+ sensor was used to record electrodermal activity related to physical discomfort and stress at 50 Hz.
Data synchronization: Python-based software ensured real-time integration of the two types of data, EMG and SCR, in all experimental conditions.

Precise sensor placement: To achieve reproducibility and precise signal acquisition, surface electromyography (sEMG) electrodes have to be placed in line with the SENIAM guidelines¹³. The bipolar Ag/AgCl electrodes were positioned on the sternocleidomastoid (midpoint between the mastoid process and sternal notch), upper trapezius (midpoint between the C7 spinous process and the acromion), and erector spinae (3 cm lateral to the L3 spinous process) muscles so that the electrodes were positioned parallel to the muscle fibers with an inter-electrode distance of 20 mm. Each site was shaved, wiped with 70% isopropyl alcohol, and abraded lightly to ensure skin impedance was less than 5 Ω. The lateral epicondyle was covered with a reference electrode. The sensors were SCR sensors, the electrodes of which were fixed to the distal phalanges of the index and middle fingers of the non-dominant hand, with a 10 min pretest calibration, where EMG and SCR baseline reference values were determined. EMG sensors were attached to the lower back, neck, and shoulders to evaluate the amplitude of muscle activation (µV) and median frequency change (Hz), which is one of the signs of muscle fatigue.

Physiological data were collected using sensors for SCR and wireless sEMG systems for muscle activity measurement, both synchronized by a Python-based data acquisition software to ensure temporal precision. All devices were calibrated before each session to maintain signal accuracy and reliability.

Figure 2: Experimental environment of the cabin (business-class). The interior layout and ergonomic features of an HSR cabin, where the emphasis was put on the comfort of passengers and space planning in the cabin. It has reclining seats that are large with privacy screens, adjustable sitting controls, and adjustable lighting. Please click here to view a larger version of this figure.

Figure 3: Experimental setup for physiological monitoring. An HSR cabin interior layout is shown, and it emphasizes the custom passenger features, ambient lighting, and ergonomic seats. It focuses on comfort, making, and practicality, which include semi-privacy of seats, spacious legroom, and an adjustable reading light. Please click here to view a larger version of this figure.

Participants and experimental design
A total of 30 healthy adult participants (15 males and 15 females) were recruited using a stratified sampling approach to ensure equal representation across business, first-class, and economy seating conditions. Participants were included if they were adults between 18 and 40 years old, in good general health, and reported no history of musculoskeletal disorders affecting the neck, shoulders, or lower back. Individuals were required to have no diagnosed neurological or systemic diseases, be able to sit comfortably throughout the experiment, and agree to follow all procedures. Participants were excluded if they had recent or ongoing neck, shoulder, or lumbar pain; had undergone spinal or upper-body surgery; had skin allergies to Ag/AgCl electrodes; were pregnant; used medications affecting neuromuscular activity; or were unable to safely complete the protocol.

The final sample consisted of 30 healthy adults (15 males and 15 females), all free of neurological and musculoskeletal impairments. The sample covered a typical range of body sizes relevant for commercial aircraft seating evaluations, and all participants were right-hand dominant to ensure consistency in electromyography measurements.

A crossover experimental design was adopted to randomly assign participants to different seating configurations so that each individual experienced business, first-class, and economy seats. During the in-seat evaluation, each participant completed four functional scenarios of equal duration within a 1-hour session. These scenarios reflect common in-flight behaviors, including resting in a relaxed seated posture, eating or drinking using the tray table, working on a laptop or tablet, and engaging in entertainment activities such as watching videos on a phone or tablet. This design allowed participants to be exposed to a range of typical cabin environments and in-flight activities, enabling controlled comparison of muscle activation patterns across conditions.

The summary of the scenarios and the frequent occurrence of passengers in each testing scenario is summarized in Figure 4.

Scenario standardization: Every practical scenario was standardized with clear instructions and posture standards to guarantee uniformity across participants and reduce confounding variables. Participants in the resting scenario reclined with their arms resting on armrests and their feet flat on the ground. In the dining setting, participants completed a standardized eating task while tray tables were raised to a consistent height of 45 cm above the seat base. In the working setting, participants executed a consistent typing job while keeping their backs in contact with lumbar support, while laptops or tablets were positioned on the tray table at a fixed height and angle. In the entertainment scenario, participants were told to keep their heads and shoulders in a neutral position and to hold their devices at a constant viewing distance. In order to guarantee adherence, researchers kept an eye on posture during each scenario and made adjustments as necessary. To acquaint participants with the standardized positions and tasks, a brief practice session was held before data collection.

Figure 4: Experiment conditions classification of scenarios. The passenger activities in HSR settings include working as in an office, eating, entertaining, sleeping, and moving around. It attracts attention to diverse activities that travelers engage in during traveling, which exemplifies the multi-purpose and multiple uses of the seating space. Please click here to view a larger version of this figure.

Physiological metrics for muscle fatigue evaluation
To enhance the assessment of muscle fatigue, we employed root mean square (RMS) and MF as the primary physiological indicators. RMS quantifies the entire electrical activity of the muscle and gives an estimate of muscle exertion, whereas MF represents fatigue-induced spectrum alterations in the EMG signal⁸. The following equations served as the foundation for these computations:

    (1)

In Eq. (1), T represents the total duration, and EMG² is the recorded EMG signal at time t. Higher RMS values indicate greater muscle exertion, while lower values suggest reduced muscle strain⁸.

   (2)

In Eq. (2), p(f) represents the power spectral density of the EMG signal. A downward shift in MF over time is indicative of increasing muscle fatigue¹⁴.

For a thorough assessment of muscle tension and physiological stress responses under various seating situations, SCR data were analyzed in conjunction with EMG. Muscle fatigue and physiological stress were measured using SCR and surface electromyography (sEMG). Electrodes were positioned on the sternocleidomastoid (neck), trapezius (shoulder), and erector spinae (lumbar) for sEMG. The raw signals underwent full-wave rectification to change negative values to positive after being band-pass filtered (20-450 Hz) to eliminate motion artefacts and low-frequency noise. The signal was smoothed with a 200 ms moving average window. The intensity of muscular activation was measured using Root Mean Square (RMS), and the progression of tiredness was identified by extracting median frequency (MF) from the power spectral density.

The autonomic changes were slow and were isolated together by recording SCR signals at a frequency of 50 Hz and low pass filtering at a frequency of 2 Hz. The tonic baseline was marked by the computation of Skin Conductance Level (SCL), and instantaneous stress reactions were recorded by removing the magnitude and delay of the phasic SCR peaks. EMG and SCR measurements were synchronized in real-time, and statistical tests, including Pearson correlations, one-way ANOVA, and repeated-measures ANOVA, were conducted to prove the correlation between physiological parameters and subjective ratings of comfort. To measure seating ergonomics in different HSR classes in different activity contexts, the pipeline ensures that the raw physiological data is converted into reliable, understandable measurements.

Data collection and processing
Before data collection, a 10 min baseline calibration was performed to ensure signal accuracy. Each participant then completed a fixed 60 min activity phase corresponding to the predefined experimental conditions. Fair exposure to different seating configurations was ensured through random seat assignment. After the trial, semi-structured interviews and subjective discomfort ratings were collected using a 1-10 Likert-type scale based on the classical methodology introduced by Likert¹⁵, providing qualitative data on perceived comfort.

To have more accurate measurements of muscle tension, the EMG differential values in all scenarios were calculated prior to and after each scenario. A reduced difference in EMG will mean more relaxed sitting and less muscle strain.

Statistical analysis and processing
Data preprocessing: Band-pass filtering (20-450 Hz), full-wave rectification, and a 200 ms moving average window were applied to extract meaningful signal trends. Raw EMG and SCR signals were first preprocessed to ensure data quality and comparability across participants. EMG signals were band-pass filtered between 20 and 450 Hz, rectified, and smoothed using a root mean square (RMS) window of 100 ms. SCR data were low pass filtered at 5 Hz and normalized relative to individual baseline recordings obtained during the pre-test calibration. Motion artifacts and outliers were removed through manual inspection and automated thresholding. The preprocessed data were then averaged over each scenario for subsequent statistical analysis.

Statistical analysis: ANOVA Comparisons: A one-way ANOVA was used to compare EMG amplitudes across seating classes, while a repeated-measures ANOVA assessed muscle fatigue trends over time. SCR Analysis: Signals were low pass filtered at 2 Hz, and peak SCR event rates (peaks per min) were compared using ANOVA. Correlation Analysis: Pearson correlation tests examined the relationships between EMG, SCR, and subjective discomfort ratings.

Qualitative analysis
The potential disparities in biomechanical strain and user experience are thematically analyzed by examining the relationship between subjective impressions and physiological results. This combination of methods provides a comprehensive, data-based approach for evaluating HSR seating ergonomics and an evidence-based platform for adaptive seat design enhancement.

Results

The results indicate high disparities in autonomic nervous activities, muscle fatigue, and overall comfort among seating classes of HSR. To provide a comprehensive picture of the impact of seat design on the physiological and psychological well-being of passengers during long flights, SCR, EMG, and scenario-based behavioral observations are integrated. These results confirm the ergonomic hypotheses presented in the introduction by supporting the theory that seat class and scenario-dependent posture have a significant inf...

Discussion

This study proposes a multimodal, scenario-based ergonomic evaluation framework that integrates electromyography (EMG), skin conductance response (SCR), and contextual behavioral analysis to examine high-speed rail (HSR) seating comfort. Unlike traditional laboratory-based seating studies that focus primarily on static posture or pressure distribution, the present work incorporates dynamic travel behaviors -- such as dining, entertainment, resting, and work -- allowing the assessment of real-time muscular demands and aut...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Adhesive EMG Electrodes (Disposable)	Noraxon	9113A
Alcohol Swabs (Sterile)	BD Medical	326895
Data Synchronization Script (Python 3.9)	Open Source	N/A
Data Synchronization Software	Custom (Python-based)	N/A	Developed in Python to integrate EMG and SCR signals in real time.
Electromyography (Surface EMG) Sensor	Delsys	Trigno Wireless EMG System
EMG Signal Processing Software	DelsysEMGworks 4.6	N/A
Physiological Data Acquisition Interface	National Instruments	USB-6001
Python Libraries (numpy, pandas, scipy, matplotlib)	Open Source (Python Software Foundation)	N/A
Questionnaire (Likert-scale)	Custom	N/A	Used to collect subjective comfort ratings (scale 1–10) after each scenario.
Seating Types (Business/First/Eco)	HSR Cabin (Real-world)	N/A	Three seating classes with varying ergonomic characteristics evaluated in-situ.
Shimmer3 GSR+ Sensor (for SCR measurement)	Shimmer Sensing	SH-GSR3+	Used to measure skin conductance response (SCR) with a 50 Hz sampling rate for stress and discomfort.
Statistical Analysis Software (IBM SPSS Statistics 26.0)	IBM	N/A
Surface Electrode Gel	Parker Laboratories	Signa Gel 300
Surface EMG Sensors	Not specified (likely Shimmer or Delsys)	N/A	Placed on shoulders, lower back, and neck; used to measure muscle activation amplitude and fatigue.
Temperature and Humidity Monitor	Testo	0560 6050
Tray Table	Integrated in HSR seats	N/A	Used in dining and working scenarios for laptop and meal placement.
Video Recording Camera (Behavioral Observation)	Canon	EOS M50
Wipes for Skin Preparation	Medline	MDS093855H