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G. del Pozo

Bio: G. del Pozo is an academic researcher from Complutense University of Madrid. The author has contributed to research in topics: Lymphangioma & Testicular torsion. The author has an hindex of 2, co-authored 3 publications receiving 157 citations.

Papers
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Journal ArticleDOI
TL;DR: It is come up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.
Abstract: A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.

188 citations

Journal ArticleDOI
TL;DR: The purpose of the study was to establish a correlation between the ultrasound and histological findings in mesenteric and omental cysts and to attempt a unified classification based on aetiological and histopathological criteria.
Abstract: We report 18 cases of intraperitoneal cystic masses in paediatric patients collected during the past 10 years in our institution. The radiological and sonographic findings are described and the histopathological correlation documented. According to the classification based on the histological characteristics of the cyst wall there were: 7 lymphangiomas, 5 duplication and enteric cysts, 2 intraperitoneal pseudocysts, 3 cases of mesenteric hydatidosis and 1 case of peritoneal tuberculosis. The purpose of the study was to establish a correlation between the ultrasound and histological findings in mesenteric and omental cysts and to attempt a unified classification based on aetiological and histopathological criteria. Despite the non-specific radiological signs, the sonographic appearance of mesenteric and omental cysts is useful in preoperative diagnosis because it allows lymphangioma, the most aggressive cyst, to be distinguished from other intraperitoneal cystic masses. Furthermore, enteric duplication cysts have specific ultrasonographic characteristics.

2 citations

Journal ArticleDOI
TL;DR: Two cases of acute scrotal involvement in two patients with HSD are reported, in one of whom the involvement was bilateral accompanied by general symptoms of HSD, and in the other it was unilateral and isolated making it difficult to differentiate from testicular torsion.
Abstract: There is only one previous reference in the radiological literature describing the ultrasound (US) appearance of male genitalia involvement in Henoch-Schonlein disease (HSD). Very rarely the “acute scrotum” may be the first symptom and could lead to a testicular torsion misdiagnosis. We report two cases of acute scrotal involvement in two patients with HSD, in one of whom the involvement was bilateral accompanied by general symptoms of HSD. In the other it was unilateral and isolated making it difficult to differentiate from testicular torsion. The US appearance, with normal or minimally affected testis, is useful in differential diagnosis.

1 citations


Cited by
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Journal ArticleDOI
10 May 2012-Sensors
TL;DR: A stress sensor based on Galvanic Skin Response (GSR), and controlled by ZigBee is designed and built, and appreciated that GSR is able to detect the different states of each user with a success rate of 76.56%.
Abstract: Sometimes, one needs to control different emotional situations which can lead the person suffering them to dangerous situations, in both the medium and short term. There are studies which indicate that stress increases the risk of cardiac problems. In this study we have designed and built a stress sensor based on Galvanic Skin Response (GSR), and controlled by ZigBee. In order to check the device's performance, we have used 16 adults (eight women and eight men) who completed different tests requiring a certain degree of effort, such as mathematical operations or breathing deeply. On completion, we appreciated that GSR is able to detect the different states of each user with a success rate of 76.56%. In the future, we plan to create an algorithm which is able to differentiate between each state.

260 citations

Journal ArticleDOI
TL;DR: This survey will examine the recent works on stress detection in daily life which are using smartphones and wearable devices and investigate the works according to used physiological modality and their targeted environment such as office, campus, car and unrestricted daily life conditions.

255 citations

Journal ArticleDOI
TL;DR: Specific facial cues, derived from eye activity, mouth activity, head movements and camera based heart activity achieve good accuracy and are suitable as discriminative indicators of stress and anxiety.

194 citations

Journal ArticleDOI
18 Apr 2019-Sensors
TL;DR: An automatic stress detection system using physiological signals obtained from unobtrusive smart wearable devices which can be carried during the daily life routines of individuals which has modality-specific artifact removal and feature extraction methods for real-life conditions.
Abstract: The negative effects of mental stress on human health has been known for decades. High-level stress must be detected at early stages to prevent these negative effects. After the emergence of wearable devices that could be part of our lives, researchers have started detecting extreme stress of individuals with them during daily routines. Initial experiments were performed in laboratory environments and recently a number of works took a step outside the laboratory environment to the real-life. We developed an automatic stress detection system using physiological signals obtained from unobtrusive smart wearable devices which can be carried during the daily life routines of individuals. This system has modality-specific artifact removal and feature extraction methods for real-life conditions. We further tested our system in a real-life setting with collected physiological data from 21 participants of an algorithmic programming contest for nine days. This event had lectures, contests as well as free time. By using heart activity, skin conductance and accelerometer signals, we successfully discriminated contest stress, relatively higher cognitive load (lecture) and relaxed time activities by using different machine learning methods.

186 citations

Journal ArticleDOI
22 Apr 2014-Sensors
TL;DR: The preliminary results obtained from the data analysis collected during the first phase of the ATREC project are presented, indicating the good classification performance exhibited when using features obtained from electrocardiographic recordings and electrical bioimpedance measurements from the thorax.
Abstract: The Spanish Ministry of Defense, through its Future Combatant program, has sought to develop technology aids with the aim of extending combatants' operational capabilities. Within this framework th ...

134 citations