Modeling the effect of postgraduate courses on soft skills: a practical approach.

Over the last decade, Higher Education has focused more of its attention toward soft skills compared to traditional technical skills. Nevertheless, there are not many studies concerning the relation between the courses followed within an academic program and the development of soft skills. This work presents a practical approach to model the effects of courses on soft skills proficiency. Multiple Membership Ordinal Logistic Regression models are trained with real data from students of the 2021, 2022, and 2023 cohorts from the general engineering program in a French Higher Education institution. The results show that attending a postgraduate course in average increases the odds of being more proficient in terms of soft skills. Nonetheless, there is considerable variability in the individual effect of courses, which suggest there can be huge differences between courses. Moreover, the data also suggest great dispersion in the students' initial soft skill proficiency.

Hierarchical classification scheme for real-time recognition of physical activities and postural transitions using smartphone inertial sensors.

This paper introduces a novel approach for real-time classification of human activities using data from inertial sensors embedded in a smartphone. We propose a hierarchical classification scheme to recognize seven classes of activities including postural transitions. Its structure has three internal nodes composed of three Support Vector Machines (SVMs) classifiers, each one is associated with a set of activities. Moreover, each SVMs is fed with a feature vector from an adapted and optimal frequency band. Experimental results conducted on a challenging publicly available dataset named SBHAR show that our method is effective and outperforms various state-of-the-art approaches. We also show the suitability of our method to recognize postural transitions.

Applying Entropy to Human Center of Foot Pressure Data to Assess Attention Investment in Balance Control.

Assessing the amount of attention invested in the control of balance is crucial when evaluating balance abilities. The purpose of the present study was to examine the relevance of applying entropy to human center of foot pressure data to assess attention investment in balance control. To achieve this goal, young healthy adults were tested in a static postural task consisting in standing as immobile as possible with their eyes closed under normal, altered (foam) and improved (ankle-foot orthosis). The center of foot pressure displacements were recorded using a force platform. Three dependent variables were computed. Results showed decreased values of velocity and displacement of Center of Pressure (CoP), indicating a less important amount of postural sway, and increased values of Sample Entropy of CoP, suggesting a less amount of attention invested in the control of bipedal posture than when the somatosensation from the foot and the ankle was normal.

Assessment of attention demand for balance control using a Smartphone: implementation and evaluation.

Dual-task paradigm studies strongly highlights the importance of considering attention demand when assessing the ability of an individual to control balance. This paper introduces the implementation of a Smartphone application for quantitative and independent assessment of attention demand for balance control. A proof-of-concept study was designed to evaluate the effectiveness of the iBalance system in assessing the attention demand for balance control. Eight young healthy adults voluntarily performed a dual-task paradigm procedure, in which they were asked to respond vocally as rapidly as possible to an unpredictable auditory stimulus while maintaining a stable seated posture and two standing postures of increasing difficulty: bipedal and unipedal. Trunk sway measurements were used as an index of postural performance, whereas reaction time measurements were used as an index of the attention demand allocated for executing the postural tasks. In line with the existing literature, results showed that, as the postural task increased in difficulty, trunk sway and attention demand used for controlling balance increased. Taken together, these results are promising, suggesting that the iBalance system could constitute a wireless, portable, lightweight, pervasive, low-cost, user-friendly Smartphone-based system for quantitative and independent assessment of attention demand for balance control suitable for home use.

Mobile Phone-Based Joint Angle Measurement for Functional Assessment and Rehabilitation of Proprioception.

Assessment of joint functional and proprioceptive abilities is essential for balance, posture, and motor control rehabilitation. Joint functional ability refers to the capacity of movement of the joint. It may be evaluated thereby measuring the joint range of motion (ROM). Proprioception can be defined as the perception of the position and of the movement of various body parts in space. Its role is essential in sensorimotor control for movement acuity, joint stability, coordination, and balance. Its clinical evaluation is commonly based on the assessment of the joint position sense (JPS). Both ROM and JPS measurements require estimating angles through goniometer, scoliometer, laser-pointer, and bubble or digital inclinometer. With the arrival of Smartphones, these costly clinical tools tend to be replaced. Beyond evaluation, maintaining and/or improving joint functional and proprioceptive abilities by training with physical therapy is important for long-term management. This review aims to report Smartphone applications used for measuring and improving functional and proprioceptive abilities. It identifies that Smartphone applications are reliable for clinical measurements and are mainly used to assess ROM and JPS. However, there is lack of studies on Smartphone applications which can be used in an autonomous way to provide physical therapy exercises at home.

Performance Evaluation of Smartphone Inertial Sensors Measurement for Range of Motion.

Over the years, smartphones have become tools for scientific and clinical research. They can, for instance, be used to assess range of motion and joint angle measurement. In this paper, our aim was to determine if smartphones are reliable and accurate enough for clinical motion research. This work proposes an evaluation of different smartphone sensors performance and different manufacturer algorithm performances with the comparison to the gold standard, an industrial robotic arm with an actual standard use inertial motion unit in clinical measurement, an Xsens product. Both dynamic and static protocols were used to perform these comparisons. Root Mean Square (RMS) mean values results for static protocol are under 0.3° for the different smartphones. RMS mean values results for dynamic protocol are more prone to bias induced by Euler angle representation. Statistical results prove that there are no filter effect on results for both protocols and no hardware effect. Smartphones performance can be compared to the Xsens gold standard for clinical research.

SVM-based multimodal classification of activities of daily living in Health Smart Homes: sensors, algorithms, and first experimental results.

By 2050, about one third of the French population will be over 65. Our laboratory's current research focuses on the monitoring of elderly people at home, to detect a loss of autonomy as early as possible. Our aim is to quantify criteria such as the international activities of daily living (ADL) or the French Autonomie Gerontologie Groupes Iso-Ressources (AGGIR) scales, by automatically classifying the different ADL performed by the subject during the day. A Health Smart Home is used for this. Our Health Smart Home includes, in a real flat, infrared presence sensors (location), door contacts (to control the use of some facilities), temperature and hygrometry sensor in the bathroom, and microphones (sound classification and speech recognition). A wearable kinematic sensor also informs postural transitions (using pattern recognition) and walk periods (frequency analysis). This data collected from the various sensors are then used to classify each temporal frame into one of the ADL that was previously acquired (seven activities: hygiene, toilet use, eating, resting, sleeping, communication, and dressing/undressing). This is done using support vector machines. We performed a 1-h experimentation with 13 young and healthy subjects to determine the models of the different activities, and then we tested the classification algorithm (cross validation) with real data.

Supervised classification of Activities of Daily Living in Health Smart Homes using SVM.

By 2050, about a third of the French population will be over 65. To face this modification of the population, the current studies of our laboratory focus on the monitoring of elderly people at home. This aims at detect, as early as possible, a loss of autonomy by objectivizing criterions such as the international ADL or the French AGGIR scales implementing automatic classification of the different Activities of Daily Living. A Health Smart Home is used to achieve this goal. This flat includes different sensors. The data from the various sensors were used to classify each temporal frame into one of the activities of daily living that has been previously learnt (seven activities: hygiene, toilets, eating, resting, sleeping, communication and dressing/undressing). This is done using Support Vector Machines. We performed an experimentation with 13 young and healthy subjects to learn the model of activities and then we tested the classification algorithm (cross-validation) on real data.

Test-retest reliability of cervicocephalic relocation test to neutral head position.

Considering the important role of the cervical joint position sense on control of human posture and locomotion, accurate and reliable evaluation of neck proprioceptive abilities appears of great importance. Although the cervicocephalic relocation test (CRT) to the neutral head position (NHP) usually is used for both research and clinical purposes, its test-retest reliability has not been clearly established yet. The purpose of the present experiment was to 1) evaluate the test-retest reliability of the CRT to NHP and 2) to determine the number of trial recordings required to ensure reliable measurements. To this aim, 40 young healthy adults performed the CRT to NHP on two separate occasions. Ten trials were performed for each rotation side. Absolute and variable errors, processed along their horizontal, vertical, and global components, were used to assess the cervical joint repositioning accuracy and consistency, respectively. Mean difference between test and retest with 95% confidence interval, intraclass correlation coefficient, and Bland and Altman graphs with limits of agreement were used as statistical methods for assessing test-retest reliability. Results show that the CRT to NHP when executed in its original form (i.e., 10 trials) has a fair to excellent reliability (ICC ranged from 0.52 to 0.81 and from 0.49 to 0.77, for absolute and variable errors, respectively); the test-retest reliability of this test increases as the number of trials used to establish subject's repositioning errors increases; and using the mean of eight trials is sufficient to ensure fair to excellent reliability of the measurements (ICC ranged from 0.39 to 0.78 and from 0.44 to 0.78, for absolute and variable errors, respectively).

Effectiveness of an electro-tactile vestibular substitution system in improving upright postural control in unilateral vestibular-defective patients.

We investigated the effects of an electro-tactile vestibular substitution system (EVSS) on upright postural control in 12 unilateral vestibular-defective patients. The underlying principle of this system consists in supplying the user with additional information about his/her head orientation/motion with respect to gravitational vertical, normally provided by the vestibular system, through electro-tactile stimulation of his/her tongue. Subjects were asked to stand as immobile as possible with their eyes closed in two No-EVSS and EVSS conditions. Reduced centre-of-foot pressure displacements were observed in the EVSS relative to the No-EVSS condition. These results, demonstrating the effectiveness of the EVSS system in improving upright postural control in unilateral vestibular-defective patients, could have implications in clinical and rehabilitative areas.

Postural destabilization induced by trunk extensor muscles fatigue is suppressed by use of a plantar pressure-based electro-tactile biofeedback.

Separate studies have reported that postural control during quiet standing could be (1) impaired with muscle fatigue localized at the lower back, and (2) improved through the use of plantar pressure-based electro-tactile biofeedback, under normal neuromuscular state. The aim of this experiment was to investigate whether this biofeedback could reduce postural destabilization induced by trunk extensor muscles. Ten healthy adults were asked to stand as immobile as possible in four experimental conditions: (1) no fatigue/no biofeedback, (2) no fatigue/biofeedback, (3) fatigue/no biofeedback and (4) fatigue/biofeedback. Muscular fatigue was achieved by performing trunk repetitive extensions until maximal exhaustion. The underlying principle of the biofeedback consisted of providing supplementary information related to foot sole pressure distribution through electro-tactile stimulation of the tongue. Centre of foot pressure (CoP) displacements were recorded using a force platform. Results showed (1) increased CoP displacements along the antero-posterior axis in the fatigue than no fatigue condition in the absence of biofeedback and (2) no significant difference between the no fatigue and fatigue conditions in the presence of biofeedback. This suggests that subjects were able to efficiently integrate an artificial plantar pressure information delivered through electro-tactile stimulation of the tongue that allowed them to suppress the destabilizing effect induced by trunk extensor muscles fatigue.