Precise morphological assessment of bone allografts is essential for successful graft-recipient matching in tissue banking. Manual measurement protocols, while standard, are labor-intensive, time-consuming, and prone to inter- and intra-observer variability. To overcome these limitations, this work presents an automated system integrated into the BeST-Graft Viewer for performing femoral allograft measurements. The proposed method replicates expert measurement strategies by defining anatomical search zones and reference planes directly within the 3D model of the femur. Reference points are automatically detected based on geometric conditions, and the corresponding anatomical parameters are computed using predefined formulas. The system was validated against manual measurements performed by three experienced experts, using 3D reconstructions of femoral grafts. Manual measurements demonstrated excellent intra- and interrater reliability, with ICC values mostly above 0.98 and all exceeding 0.89, validating their use as a reference standard. The automated system showed near-perfect agreement with the expert average (Pearson’s r = 0.99997), with no significant systematic differences observed. Moreover, the automated process required less than 15 seconds per femur with a single user interaction, in contrast to the several minutes and multiple steps needed for manual annotation. The automated measurement system provides accurate, reproducible, and highly efficient assessment of femoral allografts. It eliminates user variability and reduces measurement time by orders of magnitude. The method offers a reliable and scalable solution for integration into routine clinical workflows, and has potential for extension to other anatomical graft types.

The use of deep-learning (DL) models to support and automate medical imaging diagnostic procedures has become an ongoing focus of research and development. Despite advances in the subject, the integration of such solutions into clinical diagnostic workflows remains challenging. Especially focused on end users, the integration of image-based diagnostic functionalities and access to DL models in a single framework is key to ensuring clinical adoption and usability. This paper proposes a native integration strategy that enables the direct use of DL segmentation models within a CE-marked open-source DICOM viewer without relying on external software, containerised environments, or complex APIs. Unlike previous approaches, which often require technical expertise or infrastructure overhead, the proposed method embeds the model execution pipeline directly into the viewer via a dedicated DL module, maintaining compatibility with clinical standards and allowing model parameters to be set directly from the interface or via a configuration file. To validate the feasibility and versatility of this native integration strategy, two use cases are implemented using models trained in different DL libraries: vertebral bodies segmentation and liver segmentation. The approach proves compatible with heterogeneous model architectures, requires minimal user interaction, and preserves clinical usability without disrupting existing workflows. A new DL integration methodology is presented that combines simplicity, flexibility, and clinical readiness. The proposed framework represents a significant step towards standardised, viewer-native deployment of DL tools, facilitating their adoption in regulated healthcare environments and enabling efficient sharing and reuse of DL models across institutions.

Facial gesture interaction has gained increasing attention as a hands-free input modality for interactive systems. However, existing solutions still face limitations in adaptability, personalization, and short-term interaction design, often due to restricted gesture vocabularies, hardware dependencies, and limited adaptation to individual users. To tackle these problems, this paper presents a modular framework for integrating facial gesture recognition into gamified interactive applications, enabling intuitive hands-free control for accessibility-oriented contexts. The system supports real-time facial pose tracking using both standard webcam or virtual reality-based configurations. A lightweight calibration procedure enables user-specific gesture definition, while selective landmark masking and pose-based analysis enhance gesture discrimination and interaction stability. The framework also supports sequence-based gesture interaction, allowing the recognition of ordered pose patterns. To assess technical feasibility and interaction performance, five gesture-controlled mini-games and a Simon-says training task were implemented. A study with sixteen participants under controlled conditions showed stable gesture recognition across both hardware configurations. The webcam provided lower latency, while both configurations showed small, gesture-dependent differences in performance. Feedback collected from the short User Experience Questionnaire indicated positive usability across pragmatic and hedonic dimensions although further validation in real-world settings is needed to assess user experience beyond short-term controlled conditions. This work focuses on technical feasibility and interaction validation rather than application-specific performance.

BACKGROUND:Segmentation is a critical process in medical image interpretation. It is also essential for preparing training datasets for machine learning (ML)-based solutions. Despite technological advancements, achieving fully automatic segmentation is still challenging. User interaction is required to initiate the process, either by defining points or regions of interest, or by verifying and refining the output. One of the complex structures that requires semi-automatic segmentation procedures or manually defined training datasets is the lumbar spine. Automating the placement of a point within each lumbar vertebral body could significantly reduce user interaction in these procedures. METHOD:A new method for automatically locating lumbar vertebral bodies in sagittal magnetic resonance images (MRI) is presented. The method integrates different image processing techniques and relies on the vertebral body morphology. Testing was mainly performed using 50 MRI scans that were previously annotated manually by placing a point at the centre of each lumbar vertebral body. A complementary public dataset was also used to assess robustness. Evaluation metrics included the correct labelling of each structure, the inclusion of each point within the corresponding vertebral body area, and the accuracy of the locations relative to the vertebral body centres using root mean squared error (RMSE) and mean absolute error (MAE). A one-sample Student's t-test was also performed to find the distance beyond which differences are considered significant (α = 0.05). RESULTS:All lumbar vertebral bodies from the primary dataset were correctly labelled, and the average RMSE and MAE between the automatic and manual locations were less than 5 mm. Distances to the vertebral body centres were found to be significantly less than 4.33 mm with a p-value < 0.05, and significantly less than half the average minimum diameter of a lumbar vertebral body with a p-value < 0.00001. Results from the complementary public dataset include high labelling and inclusion rates (85.1% and 94.3%, respectively), and similar accuracy values. CONCLUSION:The proposed method successfully achieves robust and accurate automatic placement of points within each lumbar vertebral body. The automation of this process enables the transition from semi-automatic to fully automatic methods, thus reducing error-prone and time-consuming user interaction, and facilitating the creation of training datasets for ML-based solutions.

Serious games combine education and entertainment to create engaging and effective learning experiences, potentially contributing to science literacy and environmental awareness. This research aims to investigate the effectiveness of a particular serious game, H2OeduK, in educating children aged 10 to 11 years on the urban water cycle. Specifically, a study was conducted in four schools, where 140 students played the game and completed pre‐ and post‐game surveys to assess knowledge acquisition and the influence of specific socio‐demographic and gaming contextual factors. The relationship between the serious game evaluation and the knowledge acquisition scores was also explored. Results indicate that playing H2OeduK significantly enhanced children's understanding of the urban water cycle, establishing it as an effective tool for promoting water literacy and encouraging the protection of water resources. Neither gender nor play mode (individual or pair play) appeared to affect the game's effectiveness, while engaging in video gameplay positively impacted knowledge acquisition. Participants' evaluation of the game in terms of gamer experience (engagement, playfulness and self‐reported learning) did not seem to correlate with the level of learning achieved. Overall, this study underscores the potential of serious games like H2OeduK to effectively educate young learners on key sustainability challenges. Practitioner notes What is already known about this topic Educating children about the urban water cycle raises awareness and promotes responsible water usage. Serious games provide interactive and engaging ways to teach children about the urban water cycle and other environmental issues. Studies suggest that serious games can be effective in enhancing learning outcomes and promoting environmental education. What this paper adds The study provides empirical evidence on the effectiveness of H2OeduK serious game in teaching children about environmental & management concepts related to the urban water cycle. Gender does not significantly influence the acquisition of environmental knowledge through this serious game. Individual gameplay with H2OeduK is as effective as collaborative gameplay for teaching children about the urban water cycle. Implications for practice and/or policy Incorporating serious games into educational practices can be a valuable tool for teaching complex sustainability challenges to children, such as urban water cycle problems. Objective measures, like knowledge acquisition surveys, are crucial for evaluating the effectiveness of serious games in fostering learning outcomes. Further research is needed to explore the long‐term impact of serious games on knowledge retention and behavioural change and to understand their effectiveness in promoting sustainable development.

BACKGROUND:The use of technological innovations in ST elevation myocardial infarction (STEMI) care networks has been shown to be effective in improving information flow and coordination, and thus reducing the time to reperfusion. We developed a smartphone application called ODISEA to improve our STEMI care network and evaluated the results of its use. METHOD:Quasi-experimental study that compared the outcomes of STEMI suspected patients with an alert and indication for transfer to a cath lab during a previous period and a period in which the ODISEA APP was used. The main objective was to examine differences in reperfusion time and the proportion of patients with a final diagnosis other than acute coronary syndrome. RESULTS:A total of 699 patients were included (415 before and 284 during the ODISEA-APP period). No differences were observed in patient characteristics, infarct type, or acute complications. We observed a reduction in the time from diagnostic ECG to wire crossing with the use of the ODISEA APP (117 vs 102 min, p < 0.001) and a reduction in the percentage of patients with a final diagnosis other than acute coronary syndrome (17.1% vs 9.5%, p = 0.004). CONCLUSIONS:The use of the ODISEA APP in the management of patients with suspected STEMI may be useful for reducing the time from diagnostic ECG to wire crossing and the percentage of patients with a final diagnosis other than acute coronary syndrome.

Various educational resources have been incorporated into school curricula to support water education and related topics. In this paper, we present and testH(2)O-EduK, a serious game designed to introduce the urban water cycle to school children. H2O-EduK comprises seven mini-games designed to simulate the journey of pollutants generated from household activities and their impact on water quality. The game replicates this journey through pipes, wastewater treatment plants, and into rivers. To evaluate the game, we implemented two testing scenarios. In the first scenario, during last year's Science Week, H2O-EduK was installed on two devices for children to play voluntarily. After playing, 18 participants aged 10 to 12 (that passed all the mini-games) answered three questions focused on game enjoyment, mechanics, and clarity of instructions using a smiley face rating system representing five levels of satisfaction. In the second scenario, 74 students aged 10 to 12 from two schools were divided into groups of 10 to 15 members. During one-hour sessions, they individually played the game and completed pre- and post-tests. A t-test was used to evaluate answers collectively and question-by-question independently. In the first test focused on game enjoyment, mechanics, and instructions, nearly 90% of participants expressed high satisfaction with the game, while approximately 70% indicated an understanding of their tasks. The results from the school tests indicate a significant improvement in students' understanding of water cycle principles after playing the game. Post-test scores averaged 1.054 points higher than pre-test scores. Additionally, the question-by-question evaluation highlights areas of particular efficacy within the game, underscoring its potential to address specific learning needs H2O-EduK demonstrates its suitability for educational purposes, offering an engaging and effective platform for learning.

Virtual reality (VR) rehabilitation has been proven to be a very promising method to increase the focus and attention of patients by immersing them in a virtual world, and through that, improve the effectiveness of the rehabilitation. One of the biggest challenges in designing VR Rehabilitation exercises is in choosing feedback strategies that guide the patient and give the appropriate success/failure indicators, without breaking their sense of immersion. A new strategy for feedback is proposed, using non-photorealistic rendering (NPR) to highlight important parts of the exercise the patient needs to focus on and fade out parts of the scene that are not relevant. This strategy is implemented into an authoring tool that allows rehabilitators specifying feedback strategies while creating exercise profiles. The NPR feedback can be configured in many ways, using different NPR schemes for different layers of the exercise environment such as the background environment, the non-interactive exercise objects, and the interactive exercise objects. The main features of the system including the support for universal render pipeline, camera stacking, and stereoscopic rendering are evaluated in a testing scenario. Performance tests regarding memory usage and supported frames per second are also considered. In addition, a group of rehabilitators evaluated the system usability. The proposed system meets all the requirements to apply NPR effect in VR scenarios and solves all the limitations with regard to technical function and image quality. In addition, the system performance has been shown to meet the targets for low-cost hardware. Regarding authoring tool usability rehabilitators agree that is easy to use and a valuable tool for rehabilitation scenarios. NPR schemes can be integrated into VR rehabilitation scenarios achieving the same image quality as non-VR visualizations with only a small impact on the frame rate. NPR schemes are a good visual feedback alternative.

Introduction:Tissue establishments are responsible for processing, testing, preserving, storing, and distributing allografts from donors to be transplanted into recipients. In some situations, a matching process is required to determine the allograft that best fits the recipient. Allograft morphology is a key consideration for the matching process. The manual procedures applied to obtain these parameters make the process error-prone.Material and Methods:A new system to manage bone allograft-recipient matching for tissue establishments is proposed. The system requires bone allografts to be digitalized and the resulting images to be stored in a DICOM file. The system provides functionalities to: (i) manage DICOM files (registered in the PACs) from both allografts and recipients; (ii) reconstruct 3D models from DICOM images; (iii) explore 3D models using 2D, 3D, and multiplanar reconstructions; (iv) take allograft and recipient measurements; and (v) visualize and interact with recipient and allograft data simultaneously. The system has been installed in the Barcelona Tissue Bank (Banc de Sang i Teixits), which has digitalized the bone allografts to test the system.Results:A use case with a femur is presented to test all the viewer functionalities. In addition, the recipient-allograft workflow is evaluated to show the steps of the procedure where the viewer can be used.Conclusions:The bone allograft-recipient matching procedure can be optimized using software tools with functionalities to visualize, interact, and take measurements.

Sustainability education has evolved from a necessity to a responsibility, or even an obligation. Numerous awareness initiatives have been implemented to meet this, including advertising campaigns and educational materials. Serious games combine entertainment with education and offer a powerful communication strategy to engage society and promote sustainability awareness. This paper presents Pick Energy Cards, a prototype of a serious game designed to educate players on energy consumption, water waste, and environmental pollution. The study's primary focus is the evaluation process, which aims to validate the game concept and assess both its usability and playability before testing its educational impact. To achieve this, the EGameFlow usability survey has been employed. A diverse group of 24 participants, aged 18 to 60, with varying levels of video game experience, participated in the study. After playing the game, participants completed the survey. The results demonstrate that Pick Energy Cards has the potential to serve as an effective learning tool for players across all age groups.

Virtual reality (VR) and head-mounted displays (HMDs) are gaining popularity in rehabilitation. However, to be effectively integrated into clinical settings, these systems must offer advanced features such as telerehabilitation support, flexible rehabilitator-patient ratios, and real-time monitoring and interaction with virtual scenarios. To meet these requirements, this paper proposes a new system for the remote configuration and monitoring of VR-HMD rehabilitation exercises, enabling experts to interact with and manage patient-specific virtual scenarios. The system comprises two executables: one on the VR-HMD and another on an external monitoring device controlled by the expert, both coordinated by a shared Network Manager library. The paper evaluates the system by assessing time overhead (the duration when the patient is not actively engaged in rehabilitation) and system performance (including frames per second, network bandwidth usage, and monitoring effectiveness). This evaluation is compared with traditional HMD rehabilitation setups that lack rehabilitator interaction. Additionally, the system is reviewed in terms of development effort (steps and time required to adapt exercises for each monitoring method) and developers’ feedback on usability, functionality, ease of use, and future interest. Evaluation results indicate that the proposed system significantly reduces time overhead—by up to 85%—by minimizing the need to transfer the HMD between patient and rehabilitator. The system maintains performance with only a 2-5% decrease and limits network usage to under 350 kilobytes per second, ensuring fast and accurate monitoring. Developers have rated the system highly for usability and functionality, though ease of use needs improvement, and future interest depends on more streamlined development features and better documentation. Overall, the system enhances VR rehabilitation by facilitating seamless intervention, efficient monitoring, and device compatibility through low-bandwidth solutions and adjustable visual quality, thus improving control, interaction, and effectiveness.

Mirror therapy is applied to reduce phantom pain and as a rehabilitation technique in post-stroke patients. Using Virtual Reality and head-mounted displays this therapy can be performed in virtual scenarios. However, for its efficient use in clinical settings, some hardware limitations need to be solved. A new system to perform mirror therapy in virtual scenarios for post-stroke patients is proposed. The system requires the patient a standalone virtual reality headset with hand-tracking features and for the rehabilitator an external computer or tablet device. The system provides functionalities for the rehabilitator to prepare and follow-up rehabilitation sessions and a virtual scenario for the patient to perform rehabilitation. The system has been tested on a real scenario with the support of three experienced rehabilitators and considering ten post-stroke patients in individual sessions focused on upper limb motor rehabilitation. The development team observed all the sessions and took note of detected errors regarding technological aspects. Solutions to solve detected problems will be proposed and evaluated in terms of feasibility, performance cost, additional system cost, number of solved issues, new limitations, or advantages for the patient. Three types of errors were detected and solved. The first error is related to the position of the hands relative to the head-mounted display. To solve it the exercise area can be limited to avoid objectives that require turning the head too far. The second error is related to the interaction between the hands and the virtual objects. It can be solved making the main hand non-interactive. The last type of error is due to patient limitations and can be mitigated by having a virtual hand play out an example motion to bring the patient's attention back to the exercise. Other solutions have been evaluated positively and can be used in addition or instead of the selected ones. For mirror therapy based on virtual reality to be efficient in post-stroke rehabilitation the current head-mounted display-based solutions need to be complemented with specific strategies that avoid or mitigate the limitations of the technology and the patient. Solutions that help with the most common issues have been proposed.

To the Editor, The use of new technologies applied to cardiology has proven effective for the patients’ clinical improvement,1 especially in certain situations like arrhythmias, heart failure or secondary prevention.2,3 In particular, the use of smartphones applied to the healthcare networks of patients with ST-segment elevation acute myocardial infarction (STEMI) is effective to share electrocardiographic tracing and improve the coordination of the different healthcare workers involved in the management of the patients. The result is shorter primary angioplasty times.4,5 This scientific letter discusses the results of a pilot test on the working of an application for both tablets and smartphones (ODISEA APP [Myocardial Infarction Safety Transfer]) built to improve the healthcare networks of patients with STEMI (figure 1). Figure 1. Screenshots from the ODISEA APP. Geolocation, data on transfer and the infarction including images from the electrocardiogram. The primary goal of this app is to improve the coordination of the healthcare personnel involved in the management of patients with STEMI who require transfer to a PCI-capable center. This improvement should shorten primary angioplasty times and avoid unnecessary transfers. Other goals are to increase patient safety (by registering the medication administered, giving recommendations to the primary care physician, discussing doubts, etc…), improve coordination at the cath...

RGB-D sensors can be a low-cost solution for an accurate silo's content monitoring which is fundamental for its efficient management. Some reference information such as the position and orientation of the sensor with respect to the silo's geometry is fundamental for obtaining correct content measurements from acquired data. Since in real cases this information is not always known, a new method to obtain these measurements is proposed. This, taking as input sensor acquired data (represented as a point cloud), automatically computes the silo's axis to provide a new reference system from which the point cloud can be easily processed. The z-axis of this reference system coincides with the gravity axis and the xy-plane is parallel to the ground plane. It is obtained in a six-step process that exploits the silo geometry properties and an estimation of the shape tensors of the acquired points. The method has been implemented and tested on both synthetic and real silos, considering a complete silo's discharge process and different camera positions. Data acquired at each discharge has been transformed using the new reference system and compared with the silo's ground truth (manually obtained for the real silos). To evaluate the accuracy the input point cloud to adjusted point cloud average distance has been considered. In all the tests, the well-performance of the proposal has been demonstrated, achieving a maximum average distance error of less than 6 cm.

Sr. Editor: El uso de las nuevas tecnologías aplicadas a la cardiología se ha mostrado eficaz en la mejora clínica de los pacientes1, en especial en determinadas situaciones, como las arritmias, la insuficiencia cardiaca o la prevención secundaria2,3. Específicamente, el uso de los teléfonos inteligentes aplicados a las redes asistenciales de los pacientes con infarto agudo de miocardio con elevación del segmento ST (IAMCEST) es eficaz para compartir los trazados electrocardiográficos y mejorar la coordinación de los diferentes sanitarios involucrados en el tratamiento de los pacientes. El resultado es una reducción de los tiempos de angioplastia primaria4,5. En esta carta se presentan los resultados de la prueba piloto del funcionamiento de una aplicación para dispositivos móviles y tabletas (APP ODISEA [Myocardial Infarction Safety Transfer]) creada para mejorar las redes asistenciales de los pacientes con IAMCEST (figura 1). Figura 1. Capturas de pantallas de la aplicación ODISEA. Geolocalización, información del traslado y del infarto con imagen del electrocardiograma. El principal objetivo de esta aplicación es optimizar la coordinación de todos los sanitarios que entran en contacto con un paciente con IAMCEST que debe ser trasladado a un hospital con disponibilidad de angioplastia primaria. Esta mejoría debería revertir en un acortamiento de los tiempos de angioplastia primaria...

BACKGROUND Rapid primary angioplasty is the most effective reperfusion strategy for acute ST-elevation myocardial infarction (STEMI) patients. Since not all hospitals have a catheterization laboratory to perform this intervention, adequate coordination of all medical professionals involved in the management of STEMI patients from the emergency room to the hospital catheterization laboratory is necessary. OBJECTIVE Present the design and deployment of ODISEA (acronym of myOcarDial Infarction SafEtytrAnsfer), a web-based environment plus an application created to complement and support the transfer and management of STEMI patients from the first medical contact to the catheterization laboratory where the primary angioplasty will be carried out. METHOD ODISEA is an application that has been designed to improve the coordination of all health personnel involved in the management of STEMI patients, i.e., primary care hospitals, Emergency Medical Services [EMS] and cardiology departments. The application provides: (i) functionalities to register relevant information of the patients' and the administered medications, (ii) a chat to coordinate all involved personnel; (iii) treatment recommendations for the first medical contact; and (iv) a GPS-SATELLITE monitoring system to know the exact position of the ambulance during patient transfer. These features improve the coordination in the catheterization laboratory, and optimize the equipment preparation time, and also the patient accommodation procedures after primary angioplasty. ODISEA registers all treated cases for a proper follow-up. The application has been tested from September 2021 to January 2022 in the context of a pilot study in Girona that involved 98 patients and 42 professionals (11 from hospital without Cath lab availability, 21 from EMS, and 10 from the main hospital). Professionals answered a questionnaire using a five-point Likert scale (satisfaction level from 1 to 5) to assess ODISEA regarding patient management, care quality, transfer coordination, transfer effectiveness, and usefulness. Collected data was analyzed using chi-square or Fisher's exact test. Statistical significance has been considered p < 0.05. To evaluate times of first angioplasty, relevant data from 98 patients was collected and compared with data of 129 STEMI patients not treated with ODISEA. RESULTS For all the questions>70 % of answers are in the 3 to 5 range and from these, almost all the questions have 50 % of answers in the 4 and 5 range. Regarding groups of professionals only in the question related to coordination significant difference has been found for EMS professionals with respect to hospital without Cath lab availability and catheterization hospital professionals. Comparing ODISEA with no ODISEA patients it was observed an improvement in the times of first angioplasty as well as a reduction in the erroneous infarction codes activation. Patients treated with the ODISEA APP were further away from the PCI-capable center. A non-significant tendency was seen towards shorter primary angioplasty times (diagnostic electrocardiogram-guidewire passage) in the ODISEA compared to the NON ODISEA group (112 min vs 122 min; P =.3), a non-significant reduction of cases with times > 120 min (26.2 % vs 35.7 %, respectively; P =.1), and a tendency towards fewer cases eventually diagnosed as non-acute coronary syndrome (7.1 % vs 13.2 %; P =.1). CONCLUSION ODISEA is a very well-accepted application that improves the management of STEMI patients. The application is an appropriate complement to current infarction protocol.

Purpose: Lingual exercises based on tongue movements are common in speech therapy. These exercises can be tedious for patients, but gamification and virtual reality (VR) with head-mounted displays (HMD) can serve as effective strategies to enhance their motivation and engagement. However, the use of these technologies can be challenging for therapists due to a lack of technological skills. Material and Methods: A new system to support HMD-based VR for gamified tongue rehabilitation exercises is proposed. The system offers a variety of games that challenge users to achieve their goals through tongue movements and sound interaction. These games support different interaction actions that can be set by therapists using easy-to-use editors. The system also provide functionalities for patient follow-up. The system has been implemented and tested considering different technologies such as mobile devices, personal computers, and HMD complemented with an external camera to properly capture the tongue movements. Results: The therapists found the system to be user-friendly, requiring no additional support for effective utilization. The system’s versatility allows it to be used on mobile devices, as well as with augmented and virtual reality techniques, resulting in more engaging rehabilitation sessions. However, the sensibility of device movements to face detection strategies is a limiting factor of this configuration. In the case of using personal computers with HMD, better results are obtained and especially when virtual reality is considered. In this last case, it is better to consider illuminated scenarios to ensure the proper detection of facial movements. Conclusion: HMD-based VR for gamified tongue rehabilitation with ease to use editors to prepare sessions is a good strategy to improve patient engagement in tongue rehabilitation sessions.

Background:Hospital Sant Joan de Déu (Barcelona) initiated a pediatric acute home-hospitalization program. Due to high patient turnover and the health staff's lack of planning training, daily scheduling was a time-consuming task. Home-hospitalization planning is a vehicle routing problem that can be solved with a technological solution. It was therefore decided to evaluate the efficacy and necessity of the SmartMonkey.io planner.Objectives:To compare traditional manual route planning with a route optimizer, and to evaluate the technical feasibility of the implementation of a route planner into a homecare program.Methods:Eight participants (experienced homecare staff and inexperienced hospital staff) were included. Personal interviews were performed to assess their eagerness to try a technological solution to the planning problem. Objective benefits including reduced travel time (time planning, distance traveled, and time traveled) were evaluated. Paired t-test, t-test, and Pearson's correlation were used to compare manual and route planner scheduling. Participants then answered a questionnaire to assess planning difficulty and the acceptance of the route planner.Results:Homecare staff were initially reluctant to use the technology. Significant differences (P < 0.0001) in three variables were found between manual planning and the route planner. A moderate correlation between time planning and plan difficulty (r = 0.59, P < 0.0001) was found with manual planning but not with the route planner. All route planner schedules saved time and distance. No significant differences were found between expertise and planning method. It was noted that it was easy to create plans with the route planner, while difficulty with manual planning increased as more locations were added. All participants evaluated the route planning tool favorably.Conclusions:Route-planning technology saved planning time and generated better plans than manual planning. The route planner's learning curve was fast and results were obtained in the same amount of time regardless of difficulty and expertise. SmartMonkey.io also has the potential to reduce internal and environmental costs and increase staff productivity.

Patient compliance is one of the key factors for rehabilitation programs to be effective. To increase patients’ engagement game technologies and virtual reality can be applied. However, the advantages provided by these techniques are not enough to be applied in real scenarios since experts do not always have the required technological skills. To overcome this limitation, a new virtual reality-based rehabilitation system that combines virtual reality, procedural modeling, and authoring tools, is proposed. The system provides easy-to-use editors for the experts to prepare rehabilitation exercises that will take place in an expanding and varied open virtual world created using procedural generation strategies. Patients using a virtual reality headset explore this immersive virtual scenario and solve challenges by applying actions according to their rehabilitation goals and receiving success/failure feedback. While the patient interacts with the exercises through immersive virtual reality, the expert supervises the patient’s actions via a computer monitor where the exercise is displayed at the same time as in the headset. The paper presents the system and the evaluation that has been carried out to set the system configuration parameters that allow non-experts the easy creation of varied open virtual worlds for rehabilitation purposes. In addition, it collects the first impressions of rehabilitators which have been very satisfactory.