Nuevas metodologías para el reconocimiento de cambios posturales a través de sensores

Con el fin de posibilitar nuevas alternativas que permitan mitigar la complicación de las úlceras por presión, en este trabajo se presentan los resultados de investigación de la tesis doctoral, que han permitido implementar dos metodologías de reconocimiento de cambios posturales de monitoreo en tiempo real, con dispositivos vestibles inerciales no invasivos para la detección y cálculo de postura, usando técnicas de inteligencia artificial. La primera metodología está basada en un registro histórico de la actividad corporal, dataset, y por el reconocimiento de posturas en tiempo real con técnicas de Inteligencia Artificial. Por su parte, la segunda metodología comprende el uso de dispositivos vestibles inerciales en zonas no invasivas, encargados de registrar el tiempo en que la persona ha permanecido en la misma posición, la recolección de datos de personas reales en diferentes posturas, la estimación de las posturas en tiempo real se realiza mediante técnicas de inteligencia artificial.To enable new alternatives to mitigate the complication of pressure ulcers, this work presents the research results of the doctoral thesis, which have allowed the implementation of two real-time monitoring methodologies, with devices non-invasive inertial wearables for posture detection and calculation and using artificial intelligence techniques. The first methodology is based on a historical record of body activity, a dataset, and the recognition of postures in real-time with Artificial Intelligence techniques. On other hand, the second methodology includes the use of inertial wearable devices in non-invasive areas, recording the time the person has remained in the same position, the collection of data from real people in key ulcer prevention positions, the estimation of postures in real-time using artificial intelligence techniques.Tesis Univ. Jaén. Departamento de Informática. Leída el 19/11/2021

The clinical applicability of sensor technology with body position detection to combat pressure ulcers in bedridden patients

Introduction: Pressure Ulcers (PUs) are a major healthcare issue leading to prolonged hospital stays and decreased quality of life. Monitoring body position changes using sensors could reduce workload, improve turn compliance and decrease PU incidence. Method: This systematic review assessed the clinical applicability of different sensor types capable of in-bed body position detection. Results: We included 39 articles. Inertial sensors were most commonly used (n = 14). This sensor type has high accuracy and is equipped with a 2–4 hour turn-interval warning system increasing turn compliance. The second-largest group were piezoresistive (pressure) sensors (n = 12), followed by load sensors (n = 4), piezoelectric sensors (n = 3), radio wave-based sensors (n = 3) and capacitive sensors (n = 3). All sensor types except inertial sensors showed a large variety in the type and number of detected body positions. However, clinically relevant position changes such as trunk rotation and head of bed elevation were not detected or tested. Conclusion: Inertial sensors are the benchmark sensor type regarding accuracy and clinical applicability but these sensors have direct patient contact and (re)applying the sensors requires the effort of a nurse. Other sensor types without these disadvantages should be further investigated and developed. We propose the Pressure Ulcer Position System (PUPS) guideline to facilitate this.</p

The clinical applicability of sensor technology with body position detection to combat pressure ulcers in bedridden patients

Introduction: Pressure Ulcers (PUs) are a major healthcare issue leading to prolonged hospital stays and decreased quality of life. Monitoring body position changes using sensors could reduce workload, improve turn compliance and decrease PU incidence. Method: This systematic review assessed the clinical applicability of different sensor types capable of in-bed body position detection. Results: We included 39 articles. Inertial sensors were most commonly used (n = 14). This sensor type has high accuracy and is equipped with a 2–4 hour turn-interval warning system increasing turn compliance. The second-largest group were piezoresistive (pressure) sensors (n = 12), followed by load sensors (n = 4), piezoelectric sensors (n = 3), radio wave-based sensors (n = 3) and capacitive sensors (n = 3). All sensor types except inertial sensors showed a large variety in the type and number of detected body positions. However, clinically relevant position changes such as trunk rotation and head of bed elevation were not detected or tested. Conclusion: Inertial sensors are the benchmark sensor type regarding accuracy and clinical applicability but these sensors have direct patient contact and (re)applying the sensors requires the effort of a nurse. Other sensor types without these disadvantages should be further investigated and developed. We propose the Pressure Ulcer Position System (PUPS) guideline to facilitate this.</p

Commercially available pressure sensors for sport and health applications: A comparative review

Pressure measurement systems have numerous applications in healthcare and sport. The purpose of this review is to: (a) describe the brief history of the development of pressure sensors for clinical and sport applications, (b) discuss the design requirements for pressure measurement systems for different applications, (c) critique the suitability, reliability, and validity of commercial pressure measurement systems, and (d) suggest future directions for the development of pressure measurements systems in this area. Commercial pressure measurement systems generally use capacitive or resistive sensors, and typically capacitive sensors have been reported to be more valid and reliable than resistive sensors for prolonged use. It is important to acknowledge, however, that the selection of sensors is contingent upon the specific application requirements. Recent improvements in sensor and wireless technology and computational power have resulted in systems that have higher sensor density and sampling frequency with improved usability – thinner, lighter platforms, some of which are wireless, and reduced the obtrusiveness of in-shoe systems due to wireless data transmission and smaller data-logger and control units. Future developments of pressure sensors should focus on the design of systems that can measure or accurately predict shear stresses in conjunction with pressure, as it is thought the combination of both contributes to the development of pressure ulcers and diabetic plantar ulcers. The focus for the development of in-shoe pressure measurement systems is to minimise any potential interference to the patient or athlete, and to reduce power consumption of the wireless systems to improve the battery life, so these systems can be used to monitor daily activity. A potential solution to reduce the obtrusiveness of in-shoe systems include thin flexible pressure sensors which can be incorporated into socks. Although some experimental systems are available further work is needed to improve their validity and reliability

A deep learning approach for pressure ulcer prevention using wearable computing

Abstract In recent years, statistics have confirmed that the number of elderly people is increasing. Aging always has a strong impact on the health of a human being; from a biological of point view, this process usually leads to several types of diseases mainly due to the impairment of the organism. In such a context, healthcare plays an important role in the healing process, trying to address these problems. One of the consequences of aging is the formation of pressure ulcers (PUs), which have a negative impact on the life quality of patients in the hospital, not only from a healthiness perspective but also psychologically. In this sense, e-health proposes several approaches to deal with this problem, however, these are not always very accurate and capable to prevent issues of this kind efficiently. Moreover, the proposed solutions are usually expensive and invasive. In this paper we were able to collect data coming from inertial sensors with the aim, in line with the Human-centric Computing (HC) paradigm, to design and implement a non-invasive system of wearable sensors for the prevention of PUs through deep learning techniques. In particular, using inertial sensors we are able to estimate the positions of the patients, and send an alert signal when he/she remains in the same position for too long a period of time. To train our system we built a dataset by monitoring the positions of a set of patients during their period of hospitalization, and we show here the results, demonstrating the feasibility of this technique and the level of accuracy we were able to reach, comparing our model with other popular machine learning approaches

Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare—A Survey

© 2024 The Author(s). Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones’ ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.Peer reviewe

Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain

End-user assessment of an innovative clothing-based sensor developed for pressure injury prevention: a mixed-method study

This study aimed to evaluate a clothing prototype that incorporates sensors for the evaluation of pressure, temperature, and humidity for the prevention of pressure injuries, namely regarding physical and comfort requirements. A mixed-method approach was used with concurrent quantitative and qualitative data triangulation. A structured questionnaire was applied before a focus group of experts to evaluate the sensor prototypes. Data were analyzed using descriptive and inferential statistics and the discourse of the collective subject, followed by method integration and meta-inferences. Nine nurses, experts in this topic, aged 32.66 ± 6.28 years and with a time of profession of 10.88 ± 6.19 years, participated in the study. Prototype A presented low evaluation in stiffness (1.56 ± 1.01) and roughness (2.11 ± 1.17). Prototype B showed smaller values in dimension (2.77 ± 0.83) and stiffness (3.00 ± 1.22). Embroidery was assessed as inadequate in terms of stiffness (1.88 ± 1.05) and roughness (2.44 ± 1.01). The results from the questionnaires and focus groups’ show low adequacy as to stiffness, roughness, and comfort. The participants highlighted the need for improvements regarding stiffness and comfort, suggesting new proposals for the development of sensors for clothing. The main conclusions are that Prototype A presented the lowest average scores relative to rigidity (1.56 ± 1.01), considered inadequate. This dimension of Prototype B was evaluated as slightly adequate (2.77 ± 0.83). The rigidity (1.88 ± 1.05) of Prototype A + B + embroidery was evaluated as inadequate. The prototype revealed clothing sensors with low adequacy regarding the physical requirements, such as stiffness or roughness. Improvements are needed regarding the stiffness and roughness for the safety and comfort characteristics of the device evaluated.The 4NoPressure project was co-financed by the Operational Program for Competitiveness and Internationalization (COMPETE 2020) under the PORTUGAL 2020 Partnership Agreement, with support from the European Regional Development Fund (ERDF), reference number POCI-01-0247- FEDER-039869

A novel elastic sensor sheet for pressure injury monitoring: design, integration, and performance analysis

This study presents the SENSOMATT sensor sheet, a novel, non-invasive pressure monitoring technology intended for placement beneath a mattress. The development and design process of the sheet, which includes a novel sensor arrangement, material selection, and incorporation of an elastic rubber sheet, is investigated in depth. Highlighted features include the ability to adjust to varied mattress sizes and the incorporation of AI technology for pressure mapping. A comparison with conventional piezoelectric contact sensor sheets demonstrates the better accuracy of the SENSOMATT sensor for monitoring pressures beneath a mattress. The report highlights the sensor network’s cost-effectiveness, durability, and enhanced data measurement, alongside the problems experienced in its design. Evaluations of performance under diverse settings contribute to a full understanding of its potential pressure injury prediction and patient care applications. Proposed future paths for the SENSOMATT sensor sheet include clinical validation, more cost and performance improvement, wireless connection possibilities, and improved long-term monitoring data analysis. The study concludes that the SENSOMATT sensor sheet has the potential to transform pressure injury prevention techniques in healthcare.This work was carried out under the SensoMatt project, grant agreement no. CENTRO-01-0247-FEDER-070107, co-financed by European Funds (FEDER) by CENTRO2020.info:eu-repo/semantics/publishedVersio

Commercially available pressure sensors for sport and health applications: A comparative review

Pressure measurement systems have numerous applications in healthcare and sport. The purpose of this review is to: (a) describe the brief history of the development of pressure sensors for clinical and sport applications, (b) discuss the design requirements for pressure measurement systems for different applications, (c) critique the suitability, reliability, and validity of commercial pressure measurement systems, and (d) suggest future directions for the development of pressure measurements systems in this area. Commercial pressure measurement systems generally use capacitive or resistive sensors, and typically capacitive sensors have been reported to be more valid and reliable than resistive sensors for prolonged use. It is important to acknowledge, however, that the selection of sensors is contingent upon the specific application requirements. Recent improvements in sensor and wireless technology and computational power have resulted in systems that have higher sensor density and sampling frequency with improved usability – thinner, lighter platforms, some of which are wireless, and reduced the obtrusiveness of in-shoe systems due to wireless data transmission and smaller data-logger and control units. Future developments of pressure sensors should focus on the design of systems that can measure or accurately predict shear stresses in conjunction with pressure, as it is thought the combination of both contributes to the development of pressure ulcers and diabetic plantar ulcers. The focus for the development of in-shoe pressure measurement systems is to minimise any potential interference to the patient or athlete, and to reduce power consumption of the wireless systems to improve the battery life, so these systems can be used to monitor daily activity. A potential solution to reduce the obtrusiveness of in-shoe systems include thin flexible pressure sensors which can be incorporated into socks. Although some experimental systems are available further work is needed to improve their validity and reliability