There is growing interest in analyzing human movement data for clinical, sport, and ergonomic applications. Functional Data Analysis (FDA) has emerged as an advanced statistical method for overcoming the shortcomings of traditional analytic methods, because the information about continuous signals can be assessed over time. This paper takes the current literature a step further by presenting a new time scale normalization method, based on the Hilbert transform, for the analysis of functional data and the assessment of the effect on the variability of human movement waveforms. Furthermore, a quantitative comparison of well-known methods for normalizing datasets of temporal biomechanical waveforms using functional data is carried out, including the linear normalization method and nonlinear registration methods of functional data. This is done using an exhaustive database of human neck flexion-extension movements, which encompasses 423 complete cycles of 31 healthy subjects measured in two trials of the experiment on different days. The results show the advantages of the novel method compared to existing techniques in terms of computational cost and the effectiveness of time-scale normalization on the phase differences of curves and on the amplitude of means, which are assessed by Root Mean Square (RMS) values of functional means of angles, angular velocities, and angular accelerations. Additionally, the confidence intervals are obtained through a bootstrapping process.

This article presents a novel methodology conducted under controlled laboratory conditions to assess the dynamic behavior of the components of railway tracks by applying an unbalanced mass excitation force. The methodology for obtaining accurate measurements, which uses different excitation parameters, is based on an unbalanced mass device, and from these data, the transmissibility of the mass-elastomer system is estimated. For assessment of the dynamic behavior, different sine sweep rate excitations, the unbalanced mass, and background noise are considered. The experimental measurements of transmissibility with a shaker and an unbalanced mass device are performed to validate the methodology. For this, frequency-by-frequency transmissibility measurements and the swept sine were performed by the shaker, with a sine sweep from 1 to 51 Hz, using the unbalanced mass device with different sine sweep rates and unbalanced mass. The results obtained allow comparison of the transmissibility by excitation at specific frequencies and the sine sweep to validate the excitation parameters of the unbalanced mass device. Thus, a transmissibility estimation error with the sweep rate, the unbalanced mass, and the background noise is developed. By using the proposed methodology, it is possible to lower the error of the estimated transmissibility of the system with background noise.

This study investigates how three technical factors—steering wheel tilt, torque, and cabin vibration frequency—affect driver posture. Heavy-truck drivers often suffer from musculoskeletal disorders (MSDs), mainly due to poor cabin ergonomics and prolonged postures during work. In countries like Ecuador, making major structural changes to cabin design is not feasible. These factors were identified through video analysis and surveys from drivers at two Ecuadorian trucking companies. An experimental system was developed using a simplified cabin to control these variables, while posture and muscle activity were recorded in 16 participants using motion capture, inertial sensors, and electromyography (EMG) on the upper trapezius, middle trapezius, triceps brachii, quadriceps muscle, and gastrocnemius muscle. The test protocol simulated key truck-driving tasks. Data were analyzed using ANOVA (${\displaystyle p<0.05}$), with technical factors and mass index as independent variables, and posture metrics as dependent variables. Results showed that head mass index significantly affected head abduction–adduction (${\displaystyle -}$8.12 to ${\displaystyle -}$2.18°), and spine mass index influenced spine flexion–extension (${\displaystyle -}$0.38 to 6.99°). Among technical factors, steering wheel tilt impacted trunk flexion–extension (${\displaystyle -}$13.56 to 16.99°) and arm rotation (${\displaystyle -}$31.1 to 19.7°). Steering wheel torque affected arm rotation (${\displaystyle -}$30.49 to ${\displaystyle -}$6.77°), while vibration frequency influenced forearm flexion–extension (3.76 to 16.51°). EMG signals showed little variation between muscles, likely due to the protocol’s short duration. These findings offer quantitative support for improving cabin ergonomics in low-resource settings through targeted, cost-effective design changes.

A dynamic neck model is proposed for functional assessment or ergonomic studies using data obtained from conventional biomechanical tools such as video photogrammetry and force platforms. The head and neck inertial parameters are obtained through regression equations and refined through a calibration process to improve accuracy. Head movement is recorded through video photogrammetry, where marker coordinates are used to calculate finite displacements, linear and angular velocities, and accelerations. An inverse dynamics approach is used to estimate the forces and moments at the C7 vertebral level and the generated muscle power. The model was validated through an experimental study with 30 participants, where its estimates were compared to the measurements obtained from a force platform. The comparison aimed to assess the accuracy and reliability of the model. The results show excellent agreement, with a correlation of 0.976 or higher and a standard error of less than 1% of the head weight Keywords: Biomechanics, biomechanical model, neck, ergonomics, functional assessment Se presenta un modelo dinámico del cuello para su aplicación en valoración funcional o estudios de ergonomía, a partir de datos obtenidos mediante equipamiento biomecánico convencional: sistema de video fotogrametría y plataformas de fuerzas. El modelo utiliza parámetros inerciales de la cabeza y el cuello obtenidos mediante ecuaciones de regresión que se ajustan posteriormente en un proceso de calibración. El movimiento de la cabeza se registra mediante un sistema de video fotogrametría convencional. A partir de las coordenadas de los marcadores se calculan los desplazamientos finitos, velocidades y aceleraciones lineales y angulares. Las fuerzas externas se miden con una plataforma de fuerzas. Mediante un planteamiento de dinámica inversa se estiman fuerzas y momentos a nivel de C7, así como la potencia desarrollada. El modelo se ha validado mediante un estudio experimental con 30 participantes, comparando las estimaciones del modelo con las medidas en una plataforma de fuerzas. Los resultados muestran una correspondencia excelente entre las estimaciones y las medidas experimentales, con una correlación superior a 0.976 y un error estándar inferior al 1% del peso de la cabeza. Palabras clave: Biomecánica, modelo biomecánico, cuello, ergonomía, valoración funcional

The ergonomic risks associated with posture in conventional office workstations have been extensively studied, but there is limited research available on these risks in the context of home-based work environments. Most available studies rely solely on questionnaire-based statistical analyses, leaving a gap in understanding the specific conditions of home-based work environments. This study focuses on evaluating the effects of workstation conditions on posture and muscular efforts across three anatomical segments: head-neck, trunk-upper trapezius, and arm-deltoid. The analysis is conducted by simulating workstation setups commonly associated with academic activities performed by students during the COVID-19 pandemic. The conditions examined in this study include inadequate desk height, the use of chairs without armrests, and the use of laptops. Eighteen volunteers, comprising nine women and nine men, participated in experiments conducted under scenarios designed using a $2^k$ statistical approach. In all experiments, participants completed questionnaires, and text-writing activities were performed to evaluate the effects of these conditions. This research introduces a new non-invasive technique for ergonomic assessment that integrates photogrammetry and surface electromyography (sEMG) to simultaneously evaluate posture and muscular effort. The developed methodology allows precise, contactless analysis of ergonomic conditions and can be adapted for various professional and academic teleworking environments. Significant effects were observed in the posture (°) of the trunk and head, with both small and large effects identified at significance levels of p < 0.001 under the furniture conditions studied. In terms of EMG activity, moderate effects were observed at p < 0.01 levels between table height and upper trapezius activation, while small effects were detected at p < 0.05 levels between the use of chairs without armrests and neck. Similarly, small to moderate effects were observed in the arm-deltoid segment under the same furniture conditions. These findings reveal information about the posture and muscular effort patterns associated with the studied tasks, offering knowledge that can be referenced for similar tasks in other technical fields where telematics activities are performed.