Development of a Non-Contacting Muscular Activity Measurement System for Evaluating Knee Extensors Training in Real-Time.

To give people more specific information on the quality of their daily motion, it is necessary to continuously measure muscular activity during everyday occupations in an easy way. The traditional methods to measure muscle activity using a combination of surface electromyography (sEMG) sensors and optical motion capture system are expensive and not suitable for non-technical users and unstructured environment. For this reason, in our group we are researching methods to estimate leg muscle activity using non-contact wearable sensors, improving ease of movement and system usability. In a previous study, we developed a method to estimate muscle activity via only a single inertial measurement unit (IMU) on the shank. In this study, we describe a method to estimate muscle activity during walking via two IMU sensors, using an original sensing system and specifically developed estimation algorithms based on ANN techniques. The muscle activity estimation results, estimated by the proposed algorithm after optimization, showed a relatively high estimation accuracy with a correlation efficient of R2 = 0.48 and a standard deviation STD = 0.10, with a total system average delay of 192 ms. As the average interval between different gait phases in human gait is 250-1000 ms, a 192 ms delay is still acceptable for daily walking requirements. For this reason, compared with the previous study, the newly proposed system presents a higher accuracy and is better suitable for real-time leg muscle activity estimation during walking.

Evaluation of a Sensor System for Detecting Humans Trapped under Rubble: A Pilot Study.

Rapid localization of injured survivors by rescue teams to prevent death is a major issue. In this paper, a sensor system for human rescue including three different types of sensors, a CO2 sensor, a thermal camera, and a microphone, is proposed. The performance of this system in detecting living victims under the rubble has been tested in a high-fidelity simulated disaster area. Results show that the CO2 sensor is useful to effectively reduce the possible concerned area, while the thermal camera can confirm the correct position of the victim. Moreover, it is believed that the use of microphones in connection with other sensors would be of great benefit for the detection of casualties. In this work, an algorithm to recognize voices or suspected human noise under rubble has also been developed and tested.

Quantitative Laughter Detection, Measurement, and Classification-A Critical Survey.

The study of human nonverbal social behaviors has taken a more quantitative and computational approach in recent years due to the development of smart interfaces and virtual agents or robots able to interact socially. One of the most interesting nonverbal social behaviors, producing a characteristic vocal signal, is laughing. Laughter is produced in several different situations: in response to external physical, cognitive, or emotional stimuli; to negotiate social interactions; and also, pathologically, as a consequence of neural damage. For this reason, laughter has attracted researchers from many disciplines. A consequence of this multidisciplinarity is the absence of a holistic vision of this complex behavior: the methods of analysis and classification of laughter, as well as the terminology used, are heterogeneous; the findings sometimes contradictory and poorly documented. This survey aims at collecting and presenting objective measurement methods and results from a variety of different studies in different fields, to contribute to build a unified model and taxonomy of laughter. This could be successfully used for advances in several fields, from artificial intelligence and human-robot interaction to medicine and psychiatry.

Development of subliminal persuasion system to improve the upper limb posture in laparoscopic training: a preliminary study.

PURPOSE: Current training for laparoscopy focuses only on the enhancement of manual skill and does not give advice on improving trainees' posture. However, a poor posture can result in increased static muscle loading, faster fatigue, and impaired psychomotor task performance. In this paper, the authors propose a method, named subliminal persuasion, which gives the trainee real-time advice for correcting the upper limb posture during laparoscopic training like the expert but leads to a lower increment in the workload. METHODS: A 9-axis inertial measurement unit was used to compute the upper limb posture, and a Detection Reaction Time device was developed and used to measure the workload. A monitor displayed not only images from laparoscope, but also a visual stimulus, a transparent red cross superimposed to the laparoscopic images, when the trainee had incorrect upper limb posture. One group was exposed, when their posture was not correct during training, to a short (about 33 ms) subliminal visual stimulus. The control group instead was exposed to longer (about 660 ms) supraliminal visual stimuli. RESULTS: We found that subliminal visual stimulation is a valid method to improve trainees' upper limb posture during laparoscopic training. Moreover, the additional workload required for subconscious processing of subliminal visual stimuli is less than the one required for supraliminal visual stimuli, which is processed instead at the conscious level. CONCLUSIONS: We propose subliminal persuasion as a method to give subconscious real-time stimuli to improve upper limb posture during laparoscopic training. Its effectiveness and efficiency were confirmed against supraliminal stimuli transmitted at the conscious level: Subliminal persuasion improved upper limb posture of trainees, with a smaller increase on the overall workload.

Objective evaluation of oral presentation skills using Inertial Measurement Units.

Oral presentation is considered as one of the most sought after skills by companies and professional organizations and program accreditation agencies. However, both learning process and evaluation of this skill are time demanding and complex tasks that need dedication and experience. Furthermore, the role of the instructor is fundamental during the presentation assessment. The instructor needs to consider several verbal and nonverbal communications cues sent in parallel and this kind of evaluation is often subjective. Even if there are oral presentation rubrics that try to standardize the evaluation, they are not an optimal solution because they do not provide the presenter a real-time feedback. In this paper, we describe a system for behavioral monitoring during presentations. We propose an ecological measurement system based on Inertial Measurement Units to evaluate objectively the presenter's posture through objective parameters. The system can be used to provide a real-time feedback to the presenters unobtrusively.