A Systematic Review of Wearable Sensors and IoT-Based Monitoring Applications for Older Adults - a Focus on Ageing Population and Independent Living.

This review aims to present current advancements in wearable technologies and IoT-based applications to support independent living. The secondary aim was to investigate the barriers and challenges of wearable sensors and Internet-of-Things (IoT) monitoring solutions for older adults. For this work, we considered falls and activity of daily life (ADLs) for the ageing population (older adults). A total of 327 articles were screened, and 14 articles were selected for this review. This review considered recent studies published between 2015 and 2019. The research articles were selected based on the inclusion and exclusion criteria, and studies that support or present a vision to provide advancement to the current space of ADLs, independent living and supporting the ageing population. Most studies focused on the system aspects of wearable sensors and IoT monitoring solutions including advanced sensors, wireless data collection, communication platform and usability. Moderate to low usability/ user-friendly approach is reported in most of the studies. Other issues found were inaccurate sensors, battery/ power issues, restricting the users within the monitoring area/ space and lack of interoperability. The advancement of wearable technology and the possibilities of using advanced IoT technology to assist older adults with their ADLs and independent living is the subject of many recent research and investigation.

V-CarE-A Conceptual Design Model for Providing COVID-19 Pandemic Awareness: Proposal for a Virtual Reality Design Approach to Facilitate People With Persistent Postural-Perceptual Dizziness.

BACKGROUND: Virtual reality (VR) technology has been solidifying its ground since its existence, where engagement and a sense of presence are key. The contemporary field of development has captured the attention of researchers due to its flexibility and compatibility attributes. During the COVID-19 pandemic, several research outputs have shown promising prospects of continuing research in the field of VR design and development-in health sciences including learning and training. OBJECTIVE: In this paper, we aim to propose a conceptual development model named V-CarE (Virtual Care Experience) that can facilitate the understanding of pandemics when it comes to a crisis, taking precautionary measures where needed, and getting used to certain actions for preventing pandemic spread through habituation. Moreover, this conceptual model is useful to expand the development strategy to incorporate different types of users and technological aid as per need and requirement. METHODS: For a detailed understanding of the proposed model, we have developed a novel design strategy to bring awareness to the user about the current COVID-19 pandemic. VR research in health sciences has shown that with appropriate management and development, VR technology can efficiently support people with health issues and special needs, which motivated our attempts to explore the possibility of employing our proposed model to treat Persistent Postural-Perceptual Dizziness (PPPD)-a persistent nonvertiginous dizziness that could last for 3 months or more. The purpose of including patients with PPPD is to get them engaged in the learning experience and to make them comfortable with VR. We believe this confidence and habituation would help them get engaged with VR for treatment (dizziness alleviation) while practicing the preventive measures during the pandemic in an interactive environment without actually facing any pandemic directly. Subsequently, for advanced development using the V-CarE model, we have briefly discussed that even contemporary technology like internet of things (IoT) for handling devices, can be incorporated without disrupting the complete 3D-immersive experience. RESULTS: In our discussion, we have shown that the proposed model represents a significant step toward the accessibility of VR technology by creating a pathway toward awareness of pandemics and, also, an effective care strategy for PPPD people. Moreover, by introducing advanced technology, we will only further enhance the development for wider accessibility of VR technology while keeping the core purpose of the development intact. CONCLUSIONS: V-CarE-based developed VR projects are designed with all the core elements of health sciences, technology, and training making it accessible and engaging for the users and improving their lifestyle by safely experiencing the unknown. We suggest that with further design-based research, the proposed V-CarE model has the potential to be a valuable tool connecting different fields to wider communities.

A systematic review of rapid response applications based on early warning score for early detection of inpatient deterioration.

AIM: The aim of this study was to investigate the effectiveness of current rapid response applications available in acute care settings for escalation of patient deterioration. Current challenges and barriers, as well as key recommendations, were also discussed. METHODS: We adopted PRISMA review methodology and screened a total of 559 articles. After considering the eligibility and selection criteria, we selected 13 articles published between 2015 and 2019. The selection criteria were based on the inclusion of studies that report on the advancement made to the current practice for providing rapid response to the patient deterioration in acute care settings. RESULTS: We found that current rapid response applications are complicated and time-consuming for detecting inpatient deterioration. Existing applications are either siloed or challenging to use, where clinicians are required to move between two or three different applications to complete an end-to-end patient escalation workflow - from vital signs collection to escalation of deteriorating patients. We found significant differences in escalation and responses when using an electronic tool compared to the manual approach. Moreover, encouraging results were reported in extensive documentation of vital signs and timely alerts for patient deterioration. CONCLUSION: The electronic vital signs monitoring applications are proved to be efficient and clinically suitable if they are user-friendly and interoperable. As an outcome, several key recommendations and features were identified that would be crucial to the successful implementation of any rapid response system in all clinical settings.

A Novel Medical Device for Early Detection of Melanoma.

Melanoma is the deadliest form of skin cancer. Early detection of melanoma is vital, as it helps in decreasing the death rate as well as treatment costs. Dermatologists are using image-based diagnostic tools to assist them in decision-making and detecting melanoma at an early stage. We aim to develop a novel handheld medical scanning device dedicated to early detection of melanoma at the primary healthcare with low cost and high performance. However, developing this particular device is very challenging due to the complicated computations required by the embedded diagnosis system. In this paper, we propose a hardware-friendly design for implementing an embedded system by exploiting the recent hardware advances in reconfigurable computing. The developed embedded system achieved optimized implementation results for the hardware resource utilization, power consumption, detection speed and processing time with high classification accuracy rate using real data for melanoma detection. Consequently, the proposed embedded diagnosis system meets the critical embedded systems constraints, which is capable for integration towards a cost- and energy-efficient medical device for early detection of melanoma.

SVM classifier on chip for melanoma detection.

Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical images within computer-aided diagnosis systems used by skin cancer specialists to detect melanoma early and save lives. We aim to develop a medical low-cost handheld device that runs a real-time embedded SVM-based diagnosis system for use in primary care for early detection of melanoma. In this paper, an optimized SVM classifier is implemented onto a recent FPGA platform using the latest design methodology to be embedded into the proposed device for realizing online efficient melanoma detection on a single system on chip/device. The hardware implementation results demonstrate a high classification accuracy of 97.9% and a significant acceleration factor of 26 from equivalent software implementation on an embedded processor, with 34% of resources utilization and 2 watts for power consumption. Consequently, the implemented system meets crucial embedded systems constraints of high performance and low cost, resources utilization and power consumption, while achieving high classification accuracy.