Search Results (20)

This article presents an innovative system for the automated classification of postures of bedridden people using laser technology. The proposed method leverages low-cost structured light hardware and a custom algorithm to determine the side on which a person is lying. The solution prioritizes patient privacy by avoiding the capture of visual images while maintaining high accuracy in classifying postures. The system includes an enhanced hardware design with structured infrared light that is tailored for affordability and simplicity, and it incorporates an improved algorithm capable of robust posture detection. The experimental results obtained under real-world conditions validate the system’s performance and highlight its potential for deployment in clinical and home care environments. This work expands upon a previous study presented at the 6th International Conference on Application of Optics and Photonics, offering additional insights, refined methodologies, and a broader scope of validation. Full article

Stroke, amyotrophic lateral sclerosis (ALS), and Parkinson’s disease are some of the conditions that can lead to neuromotor disabilities requiring rehabilitation. To address the socio-economic burden that is amplified by the rapidly increasing elderly population, traditional rehabilitation techniques have recently been complemented by technological advancements, particularly Robot-Assisted Therapy (RAT). RAT enhances motor learning by improving both accuracy and consistency. This study proposes an innovative rehabilitation system that combines serious gaming and augmented reality (AR) with the LegUp parallel robot, developed for the spatial rehabilitation of the hip, knee, and ankle in bed-ridden patients. The system aims to improve patient outcomes and actively involve patients in their therapy. Electro-goniometers and a HoloLens 2 device are used to provide immediate feedback about the position of the patient’s joints, forming the basis of an interactive game in which the patient moves their leg to reach various targets. Two game modes were developed, each targeting different aspects of neuromotor rehabilitation, such as coordination, strength, and flexibility. Preliminary findings suggest that combining RAT with augmented reality-based serious gaming can increase patient motivation and engagement. Furthermore, the personalized and interactive nature of the therapy holds the potential to improve rehabilitation outcomes by fostering sustained engagement and effort. Full article

Low muscle strength, functional score at discharge, and complications during a ten-day rehabilitation hospital stay can affect mortality rates in bedridden geriatric patients. This was a prospective observational study in a cohort of 105 bedridden geriatric patients admitted to the Rehabilitation ward after a major illness or surgery. All participants had a severe dependency on another person (Barthel’s Index < 60). The one-year mortality rate in this cohort was 15.2%, with further subdivision according to the number of complications: 61.5% in patients with ≥3 complications during hospitalization, 17.6% in patients with two complications, 9.5% with one complication, and 3% in patients with no complications. The Barthel Index at discharge (OR = 0.95; p = 0.003) and ≥3 medical complications (OR = 8.33; p = 0.005) during rehabilitation ward stay were significant predictors for one-year mortality. The odds of one-year mortality after discharge increased eightfold in patients with ≥3 medical complications. Sarcopenia, age, and sex were not significant predictors of mortality in this cohort. The 10-day acute rehabilitation was too short to achieve progress from severe to moderate independence in 60% of patients. The Barthel Index at discharge and a number of complications affect the mortality rate. These findings provide valuable insights into the complex dynamics of mortality and functional outcomes in bedridden geriatric patients. Full article

In-bed posture classification has attracted considerable research interest and has significant potential to enhance healthcare applications. Recent works generally use approaches based on pressure maps, machine learning algorithms and focused mainly on finding solutions to obtain high accuracy in posture classification. Typically, these solutions use different datasets with varying numbers of sensors and classify the four main postures (supine, prone, left-facing, and right-facing) or, in some cases, include some variants of those main postures. Following this, this article has three main objectives: fine-grained detection of postures of bedridden people, identifying a large number of postures, including small variations—consideration of 28 different postures will help to better identify the actual position of the bedridden person with a higher accuracy. The number of different postures in this approach is considerably higher than the of those used in any other related work; analyze the impact of pressure map resolution on the posture classification accuracy, which has also not been addressed in other studies; and use the PoPu dataset, a dataset that includes pressure maps from 60 participants and 28 different postures. The dataset was analyzed using five distinct ML algorithms (k-nearest neighbors, linear support vector machines, decision tree, random forest, and multi-layer perceptron). This study’s findings show that the used algorithms achieve high accuracy in 4-posture classification (up to 99% in the case of MLP) using the PoPu dataset, with lower accuracies when attempting the finer-grained 28-posture classification approach (up to 68% in the case of random forest). The results indicate that using ML algorithms for finer-grained applications is possible to specify the patient’s exact position to some degree since the parent posture is still accurately classified. Furthermore, reducing the resolution of the pressure maps seems to affect the classifiers only slightly, which suggests that for applications that do not need finer-granularity, a lower resolution might suffice. Full article

The global relevance of pressure injury (PI) prevention technologies arise from their impact on the quality of life of people with limited mobility and the costs associated with treating these preventable injuries. The purpose of this mixed methods study is to evaluate the design of a prototype integrating Smart Health Textiles for PI prevention based on feedback from specialist nurses who care for individuals who are prone to or have PIs. This is a mixed methods study. A structured questionnaire was conducted as part of an evaluation of a prototype garment for the prevention of PIs. This questionnaire was applied during the evaluation of the prototype and afterwards focus group discussions were held with experts. Descriptive statistics techniques were used to analyze the data and thematic and integrated content analysis was conducted through concomitant triangulation. Nineteen nurses took part, aged 30 to 39 years (52.6%) and with 12.31 ± 8.96 years of experience. Participants showed that the prototype required more manipulation and physical effort, which interfered its usefulness, in addition to presenting difficulties with the openings and the material of the closure system, which interfered with the ease of use and learning. Overall satisfaction with the product was moderate, with some areas for improvement found, such as satisfaction, recommendations to colleagues, and pleasantness of use. It is concluded that areas for improvement have been found in all dimensions, including in the design of openings and the choice of materials. These findings supply significant insights for improving clothing to meet the needs of healthcare professionals and patients. Full article

Pressure injuries (PIs) are a major public health problem and can be used as quality-of-care indicators. An incipient development in the field of medical devices takes the form of Smart Health Textiles, which can possess innovative properties such as thermoregulation, sensing, and antibacterial control. This protocol aims to describe the process for the development of a new type of smart clothing for individuals with reduced mobility and/or who are bedridden in order to prevent PIs. This paper’s main purpose is to present the eight phases of the project, each consisting of tasks in specific phases: (i) product and process requirements and specifications; (ii and iii) study of the fibrous structure technology, textiles, and design; (iv and v) investigation of the sensor technology with respect to pressure, temperature, humidity, and bioactive properties; (vi and vii) production layout and adaptations in the manufacturing process; (viii) clinical trial. This project will introduce a new structural system and design for smart clothing to prevent PIs. New materials and architectures will be studied that provide better pressure relief, thermo-physiological control of the cutaneous microclimate, and personalisation of care. Full article

Bedridden patients risk presenting several problems caused by prolonged immobility, leading to a long recovery process. There is thus a need to develop solutions that ensure the implementation of physical rehabilitation programs in a controlled and interactive way. In this context, the ABLEFIT project aims to develop a medical device to physically rehabilitate bedridden patients with prolonged immobility. A partnership was established between the school of nursing, business enterprises and an engineering institute to develop a prototype. After creating the prototype, a pre-clinical experimental usability study was created using the user-centred multi-method approach (User and Human-Centered Design) to assess the device’s functionality, ergonomics and safety. The pre-clinical stage was initiated with a sample of 12 health professionals (that manipulated the device’s functionalities) and 10 end-users (who used the device). During the pre-clinical stage, the need to incorporate in the final version joint stabilizers was observed. Another important finding was the importance of the continuous monitorization of vital signs on Ablefit, namely, heart rate and SPO₂. Therefore, the development of the Ablefit system allows the monitoring of a set of variables and conditions inherent to immobility. At the same time, this device will be a dynamic solution (using gamification and simulation technologies) by generating personalized rehabilitation plans. Full article

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. Full article

Most hospitalized COVID-19 pneumonia patients are older adults and/or have nutrition-related issues. Many are bedridden in intensive care units (ICU), a well-documented cause of malnutrition, muscle wasting, and functional impairment. Objectives: To assess the effectiveness of an intensive rehabilitation program over the nutritional/functional status of patients recovering from COVID-19 pneumonia. Post-COVID-19 pneumonia patients underwent a 30-day intensive interdisciplinary rehabilitation program including a personalized nutritional intervention designed to achieve a minimum intake of 30 kcal/kg/day and 1 g protein/kg/day. The nutritional and functional status was assessed in each patient at three different moments. Each assessment included Body Mass Index (BMI), Mid Upper Arm Circumference (MUAC), Mid Arm Muscle Circumference (MAMC), Tricipital Skinfold (TSF), Hand Grip Strength (HGS), and Mini Nutritional Assessment (MNA^®). The study included 118 patients, with ages in the range 41–90 years old. BMI increased linearly over time (0.642 units, F-test = 26.458, p < 0.001). MUAC (0.322 units, F-test = 0.515, p = 0.474) and MAMC status (F-test = 1.089, p = 0.299) improved slightly, whereas TSF decreased (F-test = 1.885, p = 0.172), but all these arm anthropometry trends did not show significant variations, while HGS (4.131 units, F-test = 82.540, p < 0.001) and MNA^® (1.483 units, F-test = 217.726, p < 0.001) reported a meaningful improvement. Post-COVID-19 pneumonia patients presented malnutrition and functional impairment. An interdisciplinary rehabilitation program, including personalized nutritional intervention, was effective for post-hospital COVID-19 pneumonia nutritional/functional rehabilitation. Full article

Bedridden patients usually stay in bed for long periods, presenting several problems caused by immobility, leading to a long recovery process. Thus, identifying physical rehabilitation programs for bedridden patients with prolonged immobility requires urgent research. Therefore, this scoping review aimed to map existing physical rehabilitation programs for bedridden patients with prolonged immobility, the rehabilitation domains, the devices used, the parameters accessed, and the context in which these programs were performed. This scoping review, guided by the Joanna Briggs Institute’s (JBI) methodology and conducted in different databases (including grey literature), identified 475 articles, of which 27 were included in this review. The observed contexts included research institutes, hospitals, rehabilitation units, nursing homes, long-term units, and palliative care units. Most of the programs were directed to the musculoskeletal domain, predominantly toward the lower limbs. The devices used included lower limb mobilization, electrical stimulation, inclined planes, and cycle ergometers. Most of the evaluated parameters were musculoskeletal, cardiorespiratory, or vital signs. The variability of the programs, domains, devices and parameters found in this scoping review revealed no uniformity, a consequence of the personalization and individualization of care, which makes the development of a standard intervention program challenging. Full article

Pressure ulcers (PU) are one of the most frequent hazards of long-term bedridden patients. With the continuous increase of aging, the number of long-term bedridden disabled and semi-disabled elderly people is increasing. At the same time, there is a serious shortage of professional pressure ulcer nursing staff. There is also a lack of flexible turning equipment for PU prevention. The research in the field of pressure ulcer prevention at home and abroad is carried out steadily, and the equipment for turning over by pneumatic or mechanical drive is developed. However, these devices often have insurmountable defects, such as complex structure, cost constraints, difficult control, weak body feeling, and so on. Under these circumstances, a set of pneumatic turnover mattresses based on clinical nursing methods have been developed. The mattress is divided into a turnover area and two support areas. The turnover airbag is linked with the support airbag to improve the patient’s comfort when passively turning over. The turnover amplitude and interval can be adjusted to provide a personalized turnover experience for bedridden patients. To improve the safety of the turning mattress during automatic turning, we also add a temperature sensor based on the principle of infrared reflection to monitor the status of bedridden patients, which can realize real-time temperature measurement, monitoring of getting out of bed and monitoring of the turning process. Full article

Bedridden patients usually stay in bed for long periods, presenting several motor problems caused by immobility, such as reductions in muscle mass, bone mineral density and physical impairment, resulting in a long recovery process. Thus, identifying physical rehabilitation programs for bedridden patients with prolonged immobility is a matter of urgent research for a solution that will help health professionals and stakeholders to develop more adjusted programs and identify possible gaps. To date, no previous scoping reviews addressing this purpose have been found. This scoping review will be guided by the Joanna Briggs Institute (JBI) methodology, will focus on physical rehabilitation programs for bedridden patients with prolonged immobility and aims to map the programs, the devices used, and the parameters assessed. A relevant set of electronic databases and grey literature will be searched. Data extraction will be conducted using a tool developed by the research team that will address the review objectives and questions. Data synthesis will be presented in tabular form and a narrative summary aligned with the review’s objective. This scoping review will contribute to the improvement of clinical practice, identifying key challenges that might justify the need to develop new programs suitable in clinical and organizational contexts. Full article

An e-textile mat with capacitive textile sensors was designed and manufactured to monitor body position and prevent decubitus ulcers in the case of bedridden people. The sensors were incorporated through a process of machine embroidery with electrically conductive threads. A new production method for the conductive threads is still expected to be developed, resulting in good conductive properties, high wear resistance and durability. Samples of five variants of motifs without cross-stitching were studied, and the capacity and electrical resistance were determined experimentally. A prototype of the e-textile mat was made with a motif showing the best ratio between the inserted thread and the measured capacity. A hardware solution and a software application for collecting, processing and visualising the received information were developed. Tests were performed in real conditions, which clearly showed that the designed e-textile mat could be successfully applied for non-invasive and continuous control of the position of the human body in a supine position to prevent decubitus ulcers. Full article

This article presents the design of a low-cost Wireless Body Sensor Network (WBSN) for monitoring vital signs including a low-cost smart wristwatch that contains an ESP-32 microcontroller and three sensors: heart rate (HR), blood pressure (BP) and body temperature (BT), and an Internet of Things (IoT) platform. The vital signs data are processed and displayed on an OLED screen of the patient’s wristwatch and sent the data over a wireless connection (Wi-Fi) and a Cloud Thing Board system, to store and manage the data in a data center. The data can be analyzed and notified to medical staff when abnormal signals are received from the sensors based on a set parameters from specialists. The proposed low-cost system can be used in a wide range of applications including field hospitals for asymptotic or mild-condition COVID-19 patients as the system can be used to screen those patients out of symptomatic patients who require more costly facilities in a hospital with considerably low expense and installation time, also suitable for bedridden patients, palliative care patients, etc. Testing experiments of a 60-person sample size showed an acceptable accuracy level compared with standard devices when testing with 60 patient-samples with the mean errors heart rate of 1.22%, systolic blood pressure of 1.39%, diastolic blood pressure of 1.01%, and body temperature of 0.13%. According to testing results with 10 smart devices connected with the platform, the time delay caused by the distance between smart devices and the router is 10 s each round with the longest outdoor distance of 200 m. As there is a short-time delay, it does not affect the working ability of the smart system. It is still making the proposed system be able to show patient’s status and function in emergency cases. Full article