1,721,083 research outputs found
A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue
No full textMean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and disadvantages. Previous works studied how the implementation settings can influence the performance of these techniques; nevertheless, the estimation results have never been fully evaluated when the power density spectrum is in a low-frequency zone, as happens to the surface electromyography (sEMG) spectrum during muscle fatigue. The latter is therefore the objective of this study that has compared the Welch and the autoregressive parametric approaches on synthetic sEMG signals simulating severe muscle fatigue. Moreover, the sensitivity of both the approaches to the observation duration and to the level of noise has been analyzed. Results showed that the mean frequency greatly depends on the noise level, and that for Signal to Noise Ratio (SNR) less than 10dB the errors make the estimate unacceptable. On the other hand, the error in calculating the median frequency is always in the range 2–10 Hz, so this parameter should be preferred in the tracking of muscle fatigue. Results show that the autoregressive model always outperforms the Welch technique, and that the 3rd order continuously produced accurate and precise estimates; consequently, the latter should be used when analyzing severe fatiguing contraction
Estimation of mean and median frequency from synthetic sEMG signals: Effects of different spectral shapes and noise on estimation methods
No full textThe detection of electrical signs of muscle fatigue passes through the choice of appropriate spectral estimation techniques for the extraction of parameters such as Mean and Median Frequency from surface myoelectric signals. Unfortunately, despite the huge number of contributions using various spectral techniques to process signals recorded in fatiguing protocols, there is no agreement on the method that works best, and to our knowledge, the performance of the estimation techniques has been evaluated only on a limited range of spectral shapes. To study the fatigue phenomenon, it is important to consider the range of variation of the spectral parameters and then the different shapes assumed by the signal spectrum. In this work, the latter characteristics have been used to simulate synthetic myoelectric signals whose Power Spectral Density has been estimated in different noise conditions by using the following techniques: a) indirect technique by the estimation of the autocorrelation function; b) direct technique by the Welch estimation method with special attention to the window functions for signal segmentation; c) Burg autoregressive approach with special attention to the model order. The main result, after assessing that Burg's approach outperforms all the other techniques for all the examined conditions, outlines that the model's order, despite ranging between 6 and 12, depends on the spectral shape and affects the estimation of the Median Frequency. This partially overwrites previous results of the literature and provides the useful recommendation to choose, among the spectral estimation techniques, the most adaptive to the dynamics of the fatigue process
A non-intrusive system for seated posture identification
No full textIn this contribution a system for seated posture identification is presented. The assessment tools is based on an office-chair equipped with sensors. In more details, a set of textile pressure sensors has been placed on a chair both on the chair backrest and on the seat. The position of the sensors has been selected for maximizing the possibility of sensing minimum variations of the subject's posture. To validate the system, an extensive subjective experiment has been performed in which the subject undergoes an increasing stress-level test. The collected results show that this instrument is effective in assessing the attention/fatigue of a subject in seating condition by the analysis of body posture
Linking head and neck posture with muscular activity and perceived discomfort during prolonged smartphone texting
No full textProlonged use of the smartphone for texting was studied on a sample of 17 healthy young adult participants (11 females), who were asked to type interactively on a handheld device while standing and sitting. Upper body kinematics ad upper trapezius surface EMG were recorded to capture parameters of joint kinematics and muscular activity, which were then compared with self-reported indicators of discomfort through the Borg's CR 10 scale questionnaire. The results indicated that, while showing a similar postural strategy in both conditions that is assumed to be controlled by the visual system to maintain a constant viewing distance from the device, the participants adopted a “stiffer” posture of the head and neck during standing than when sitting, with a direct correlation between upper trapezius muscle activity, neck angle and perceived discomfort. The evidence obtained in this study highlights the importance of monitoring muscle activity and head and neck kinematics, to assess the biomechanical risk factors of neuromuscular disorders associated with smartphone overuse
Estimating Spatial Gait Parameters from the Planar Covariation of Lower Limb Elevation Angles: a Pilot Study
No full textWhen characterizing human gait control strategies, theories based on the modularity of the neuromuscular system have been proven to be powerful in providing a compact description of the gait patterns. The planar covariation law of lower limb elevation angles has been proposed as a compact, modular description of gait kinematics. In this paper, we exploit this model for characterizing healthy subjects' spatial gait parameters during walking at different speeds, one self-selected and one slightly slower than the subject's comfortable pace. Different geometrical features have been calculated over the gait loop, that is the planar loop defined by the covariation of the thigh, shank and foot elevation angles. A correlation analysis has been carried out between these features and classical gait spatial parameters (step length, step width, stride length and foot clearance) by training a linear regressor on the dataset comprising both speeds. The results from this analysis have highlighted a correlation with some spatial gait parameters across the two speed conditions, indicating that this compact description of kinematics unravels a significant biomechanical meaning. These results can be exploited to guide the control mechanisms of external assistive devices, such as prostheses or exoskeletons, based purely on the measurement of few relevant kinematic quantities of the lower limb segments
A new microcontroller-based system to optimize the digital conversion of signals originating from load cells built-in into pedals
No full textDuring cycling, the measurement of forces exerted on the pedal is used to monitor the level of training and to maximize the efficiency of pedaling. In rehabilitation, the force measurement can be used to monitor the functional recovery of a patient during a therapy. In these situations, it is useful to quantify with high resolution these variables. In this work a solution to remove the DC offset at the input of an AD converter for force measurement systems, based on strain gauges load cells, is presented. This circuit has been integrated into a device used in sports and in rehabilitation contexts, that relies on a couple of cycling instrumented pedals. The system designed in this work aims at obtaining these results in a simple way and with its complete integration into the control circuit of the instrumented pedals
Modalities of sequential human robot collaboration trigger different modifications of trunk oscillations
No full textIntroduction: Human robot collaboration is quickly gaining importance in the robotics and ergonomics fields due to its ability to reduce biomechanical risk on the human operator while increasing task efficiency. The performance of the collaboration is typically managed by the introduction of complex algorithms in the robot control schemes to ensure optimality of its behavior; however, a set of tools for characterizing the response of the human operator to the movement of the robot has yet to be developed. Methods: Trunk acceleration was measured and used to define descriptive metrics during various human robot collaboration strategies. Recurrence quantification analysis was used to build a compact description of trunk oscillations. Results and discussion: The results show that a thorough description can be easily developed using such methods; moreover, the obtained values highlight that, when designing strategies for human robot collaboration, ensuring that the subject maintains control of the rhythm of the task allows to maximize comfort in task execution, without affecting efficiency
Smartphone-Based Answering to School Subject Questions Alters Gait in Young Digital Natives
No full textSmartphone texting while walking is a very common activity among people of different ages, with the so-called “digital natives” being the category most used to interacting with an electronic device during daily activities, mostly for texting purposes. Previous studies have shown how the concurrency of a smartphone-related task and walking can result in a worsening of stability and an increased risk of injuries for adults; an investigation of whether this effect can be identified also in people of a younger age can improve our understanding of the risks associated with this common activity. In this study, we recruited 29 young adolescents (12 ± 1 years) to test whether walking with a smartphone increases fall and injuries risk, and to quantify this effect. To do so, participants were asked to walk along a walkway, with and without the concurrent writing task on a smartphone; several different parameters linked to stability and risk of fall measures were then calculated from an inertial measurement unit and compared between conditions. Smartphone use determined a reduction of spatio-temporal parameters, including step length (from 0.64 ± 0.08 to 0.55 ± 0.06 m) and gait speed (1.23 ± 0.16 to 0.90 ± 0.16 m/s), and a general worsening of selected indicators of gait stability. This was found to be mostly independent from experience or frequency of use, suggesting that the presence of smartphone activities while walking may determine an increased risk of injury or falls also for a population that grew up being used to this concurrency
A focus on quantitative methods to assess human factors in collaborative robotics
No full textThe advent of Industry 4.0 has transformed manufacturing by incorporating industrial robots to boost productivity and quality while cutting costs. Human-Robot Collaboration (HRC) is central to this shift, emphasizing seamless cooperation between humans and robots in shared workspaces. Evaluating the impact of such collaboration on human operators is crucial for efficiency, safety, and well-being. This systematic review explores methodologies for assessing human factors in HRC environments, spanning psychological, cognitive, and physical realms. Various evaluation methods have been identified, from subjective questionnaires to objective measurements. While subjective methods are the standard (especially questionnaires), there is a growing trend towards integrating physiological and physical measurements. The blend of subjective and objective methods offers a holistic understanding of human-robot interaction. This review adopts a more technical-oriented approach in the assessment of human factors in HRC. As a result, it consolidates existing methodologies and suggests avenues for further research, highlighting the significance of this assessment for enhancing productivity, safety, and well-being in industrial settings
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