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Fraunhofer Center for Assistive Information and Communication Solutions, Portugal
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6 Papers

Leveraging Deep Neural Networks for Automatic and Standardised Wound Image Acquisition

Topics: Decision Support Systems; Mobile Health Monitoring; Computer Vision and Healthcare Robotics; Health Information Systems; Data and Real-Time Analytics

Authors: Ana Filipa Sampaio 1 , Pedro Alves 1 , Nuno Cardoso 1 , Paulo Alves 2 ; 3 , Raquel Marques 3 , Pedro Salgado 4 and Maria Vasconcelos 1

Affiliations: 1 Fraunhofer Portugal AICOS, Porto, Portugal , 2 School of Nursing Department, Universidade Católica Portuguesa (UCP), Porto, Portugal , 3 Centre for Interdisciplinary Research in Health, Instituto de Ciências da Saúde, UCP, Porto, Portugal , 4 F3M Information Systems, S.A, Portugal

Digital Object Identifier: 10.5220/0012031200003476

Proceedings of ICT4AWE 2023, ISBN: 978-989-758-645-3

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Wound monitoring is a time-consuming and error-prone activity performed daily by healthcare professionals. Capturing wound images is crucial in the current clinical practice, though image inadequacy can undermine further assessments. To provide sufficient information for wound analysis, the images should also contain a minimal periwound area. This work proposes an automatic wound image acquisition methodology that exploits deep learning models to guarantee compliance with the mentioned adequacy requirements, using a marker as a metric reference. A RetinaNet model detects the wound and marker regions, further analysed by a post-processing module that validates if both structures are present and verifies that a periwound radius of 4 centimetres is included. This pipeline was integrated into a mobile application that processes the camera frames and automatically acquires the image once the adequacy requirements are met. The detection model achieved mAP@.75IOU values of 0.39 and 0.95 for wound and marker detection, exhibiting a robust detection performance for varying acquisition conditions. Mobile tests demonstrated that the application is responsive, requiring 1.4 seconds on average to acquire an image. The robustness of this solution for real-time smartphone-based usage evidences its capability to standardise the acquisition of adequate wound images, providing a powerful tool for healthcare professionals.

Automated Mobile Image Acquisition of Macroscopic Dermatological Lesions

Topics: Mobile Technologies for Healthcare Applications; Pattern Recognition and Machine Learning; eHealth Applications

Authors: Dinis Moreira , Pedro Alves , Francisco Veiga , Luís Rosado and Maria João M. Vasconcelos

Affiliation: Fraunhofer Portugal AICOS, Porto, Portugal

Digital Object Identifier: 10.5220/0010234201220132

Proceedings of HEALTHINF 2021/BIOSTEC, ISBN: 978-989-758-490-9

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The incidence of skin cancer has been rising every year translating in high economic costs. The development of mobile teledermatology applications that can contribute for the standardization of image acquisition can facilitate early diagnosis. This paper presents a new methodology for real-time automated image acquisition of macroscopic skin images via mobile devices. It merges an automated image focus assessment that uses a feature-based machine learning approach with segmentation of dermatological lesions using computer vision techniques. It also describes the datasets used to develop and evaluate the proposed approach: 3428 images from one dataset purposely collected using different mobile devices for the focus assessment component, and a total of 1380 images from two other datasets available on the literature to develop the segmentation approach. The best model for automatic focus assessment of preview images and acquired picture achieved an overall accuracy of 88.3% and 86.8%, respectively. The segmentation approach attained a Jaccard index of 85.81% and 68.59% for SMARTSKINS and Dermofit datasets, respectively. The developed algorithms present a fast processing time that is suitable for real-time usage in medium and high performance smartphones. These findings were also validated by implementing the proposed methodology within an android application demonstrating promising results.

SousChef: Mobile Meal Recommender System for Older Adults

Topics: Mobile Collaboration Technologies; Systems to Encourage Healthy Lifestyles; Mobile Health Monitoring; Personalized Interfaces; Intelligent Companions

Authors: David Ribeiro 1 , João Machado 1 , Jorge Ribeiro 1 , Maria João M. Vasconcelos 1 , Elsa F. Vieira 2 and Ana Correia de Barros 3

Affiliations: 1 Fraunhofer Portugal AICOS, Portugal , 2 REQUIMTE, Institute of Engineering of Porto and Polytechnic Institute of Porto, Portugal , 3 CRPG - Gaia Vocational Rehabilitation Centre, Portugal

Digital Object Identifier: 10.5220/0006281900360045

Proceedings of ICT4AWE 2017, ISBN: 978-989-758-251-6

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Nowadays, following a healthy diet is a challenge, either due to the large variety of food and ingredient combination possibilities or due to the lack of knowledge required to make healthy choices. This problem is even more patent amongst older adults. Although some recommender systems and applications have been proposed with aim to monitor calorie consumption and/or to suggest healthy recipes to general consumers, no similar solution was yet presented focused on older adults’ needs. In this work, a mobile meal recommender system, SousChef, for this target group is presented. This system is capable of creating a personalized meal plan based on the information provided by the user, including the anthropometric measures, personal preferences and activity level. The nutritional recommendations and the application was thought and designed for older adults, presenting friendly user interfaces and following the guidelines of a nutritionist. Tests with users were conducted in order to ascertain recipe and nutritional plan suitability as well as usability of the mobile application. Results showed that more than 70% of the older adult participants were satisfied with the meal plan suggestions and with the simplicity of the SousChef application.

μSmartScope: 3D-printed Smartphone Microscope with Motorized Automated Stage

Topics: Emerging Technologies; Biomedical Instrumentation; Biomedical Equipment; Imaging and Visualization Devices

Authors: Luís Rosado 1 , João Oliveira 1 , Maria João M. Vasconcelos 1 , José M. Correia da Costa 2 , Dirk Elias 1 and Jaime S. Cardoso 3

Affiliations: 1 Fraunhofer Portugal AICOS, Portugal , 2 Instituto Nacional de Saúde Dr. Ricardo Jorge, Portugal , 3 INESCTEC and University of Porto, Portugal

Digital Object Identifier: 10.5220/0006155800380048

Proceedings of BIODEVICES 2017/BIOSTEC, ISBN: 978-989-758-216-5

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Microscopic examination is currently the gold standard test for diagnosis of several neglected tropical diseases. However, reliable identification of parasitic infections requires in-depth train and access to proper equipment for subsequent microscopic analysis. These requirements are closely related with the increasing interest in the development of computer-aided diagnosis systems, and Mobile Health is starting to play an important role when it comes to health in Africa, allowing for distributed solutions that provide access to complex diagnosis even in rural areas. In this paper, we present a 3D-printed microscope that can easily be attached to a wide range of mobile devices models. To the best of our knowledge, this is the first proposed smartphone-based alternative to conventional microscopy that allows autonomous acquisition of a pre-defined number of images at 1000x magnification with suitable resolution, by using a motorized automated stage fully powered and controlled by a smartphone, without the need of manual focus of the smear slide. Reference smears slides with different parasites were used to test the device. The acquired images showed that was possible to visually detect those agents, which clearly illustrate the potential that this device can have, specially in developing countries with limited access to healthcare services.

Automatic Segmentation Methodology for Dermatological Images Acquired via Mobile Devices

Topics: Telemedicine; Design and Development Methodologies for Healthcare IT; Mobile Technologies for Healthcare Applications

Authors: Luís Rosado and Maria Vasconcelos

Affiliation: Fraunhofer Portugal AICOS, Portugal

Digital Object Identifier: 10.5220/0005178302460251

Proceedings of HEALTHINF 2015/BIOSTEC, ISBN: 978-989-758-068-0

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Nowadays, skin cancer is considered one of the most common malignancies in the Caucasian population, thus it is crucial to develop methodologies to prevent it. Because of that, Mobile Teledermatology (MT) is thriving, allowing patients to adopt an active role in their health status while facilitating doctors to early diagnose skin cancers. Skin lesion segmentation is one of the most important and difficult task in computerized image analysis process, and so far the attention is mainly turned to dermoscopic images. In order to turn MT more accurate, it is therefore fundamental to develop simple segmentation methodologies specifically designed for macroscopic images or images acquired via smartphones, which is the main focus of this work. The proposed method was applied in 80 images acquired via smartphones and promising results have been achieved: a mean Jaccard index of 81%, mean True Detection Rate of 96% and mean Accuracy around 98%. The major goal of this work is to develop a mobile application easily accessible for the general population, with the aim of raise awareness and help both patients and doctors in the early diagnosis of skin cancers.
Collapse Button Related Ontology Subjects/Areas/Topics (11)
Biomedical Engineering

Health Information Systems

Neurotechnology, Electronics and Informatics

Design and Development Methodologies for Healthcare IT

Mobile Technologies

Software Engineering

Distributed and Mobile Software Systems

Mobile Technologies for Healthcare Applications

Telemedicine
Health Engineering and Technology Applications

Neural Rehabilitation

Needs and Opportunities in Ambient Assisted Living in Portugal

Authors: Ricardo Vardasca 1 , Liliana Ferreira 2 and Ricardo Simoes 3

Affiliations: 1 University of Minho, Portugal , 2 Fraunhofer AICOS Portugal, Portugal , 3 University of Minho and Polytechnic Institute of Cávado and Ave, Portugal

Digital Object Identifier: 10.5220/0003889201000108

Proceedings of AAL 2012/BIOSTEC, ISBN: 978-989-8425-93-5

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The exponential raise in the age dependency rate together with the difficulties in having conventional care solutions opens the space for the appearance and development of innovative Ambient Assisted Living (AAL) solutions. However, the development of these solutions requires a thorough understanding of user needs and wills. In this paper we present the scenarios being adopted in the context of AAL projects, as well as the products and services current available in each of the considered utilization scenarios. The needs of the Portuguese AAL users are analyzed through the discussion of some preliminary results from a survey targeted at the Portuguese population over 55 years old. These results will be used to characterize the needs and establish the readiness and willingness of elder Portuguese population in using AAL solutions.

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