Low level light therapy in the management of paediatric oral and oropharyngeal mucositis

Oral and oropharyngeal mucositis is a common, debilitating condition experienced by patients undergoing oncology treatment. There are many different management strategies, with low level light therapy (LLLT) an emerging field. Ongoing research on the topic of LLLT for mucositis has resulted in LLLT being included in national clinical guidelines. The number of centres currently using LLLT for paediatric patients with oropharyngeal mucositis is growing, with Glasgow having successfully used this treatment method for a number of years. Across medicine and dentistry, LLLT is coming to the fore and is a treatment modality of which we should all be aware. CPD/Clinical Relevance: New technologies and treatment modalities are areas with which practitioners should stay up to date. Low level light therapy continues to be a growing research field

Assessing the provision of prevention in the care pathway for children undergoing dental extractions under general anaesthetic at the Royal Hospital for Children, Glasgow: a qualitative systems-level needs assessment.

Introduction Although Scotland has made advances in the last decade in dental prevention and in tackling oral health inequalities, many children still develop dental caries, and many subsequently require a Dental General Anaesthetic (DGA) for extractions. These DGAs are undesirable given the impact on the patient, family and NHS. National guidelines recommend that a DGA is undertaken only if there are no other options for treatment. When children require a second ‘repeat’ DGA, or siblings consequently require a DGA, it suggests that current prevention protocols are not working. These children are slipping through the net. Both strategic and front-line stakeholders raised concerns that the care pathway for children undergoing general anaesthetics (GAs) for dental extractions at the Royal Hospital for Children, NHS Greater Glasgow and Clyde (RHCG) was not aligned to prevention, and was not best supporting these vulnerable families to improve and maintain oral health. Aims and Objectives The overarching aim of this study was to assess provision of dental prevention in the RHCG DGA care pathway, with a view to making recommendations at a local level on how to optimise prevention. The objectives were (i) to assess the pathway of care in relation to prevention and, if required, to investigate what opportunities existed to integrate further prevention into the pathway; (ii) to explore the pathway’s wider context including national policies and programmes which may support prevention, and (iii) to explore some examples of good preventive practice for DGA pathways locally and in other Scottish NHS boards. Methods This work was undertaken in two phases. An initial scoping exercise mapped the existing pathway of care and any child health policy or programme which could support prevention. A qualitative systems-level needs assessment subsequently explored both the views of stakeholders involved in providing care for these children, and individuals in wider child health policy and programmes, to ascertain how prevention could be better integrated into the pathway. Results Key findings illustrated minimal prevention currently being provided in the pathway of care and limited linkages with wider policy and programmes. Stakeholders recognised a need for change. Good preventive practice was highlighted in two external NHS Health Boards and one DGA pathway of care within NHS GGC. Suggestions for integrating prevention focused on transforming the pathway ethos towards multi-agency, tailored prevention and a whole-family approach. Clinical prevention suggestions were made within a proposed ‘Prevention Pathway’ model of tailored care. Potential strategies were suggested as to how to maximise patient engagement including local access clinics and liaising with support workers and the ‘Named Person’. Anticipated barriers to change included challenges with collaborative working, stakeholder attitudes, service pressures and board-level challenges such as the size of NHS GGC. Suggestions to overcome these challenges included training and education of stakeholders, consideration of an Early Years Collaborative pilot to assess changes within a local setting, improved communication and the development of a multi-agency working group to lead and affect change in the ‘Prevention Pathway’. Conclusion This study found that prevention was not currently embedded within the pathway of care, particularly at paediatric assessment and on the day of DGA, but that many positive steps could be taken to improve the provision of prevention at all stages; from direct clinical prevention to the wider multi-agency response. Wider health inequalities must not be forgotten in efforts to engage these vulnerable families, and an ethos of prevention and early intervention must be entrenched in current practice to reduce the number of children requiring preventable general anaesthetics

Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project

SmartVista: Smart Autonomous Multi Modal Sensors for Vital Signs Monitoring

Cardiovascular diseases (CVD) remain the leading cause of mortality and a major cause of morbidity in Europe. Every year there are more than 6 million new cases of CVD in the EU and more than 11 million in Europe as a whole. With almost 49 million people living with the disease in the EU, the cost to the EU economies is 210 billion EUR a year. There is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviours which, in extreme cases, can lead to sudden death. The objective of the Smart Autonomous Multi Modal Sensors for Vital Signs Monitoring (SmartVista) project is to develop and demonstrate a next generation, cost-effective, smart multimodal sensing platform to reduce incidences of sudden death caused by CVD, and will contribute to the EU vision of an Internet of Things for healthcare. The key innovation in SmartVista is to integrate 1D/2D nanomaterials based sensors to monitor the heart, thermoelectric energy harvesters to extract energy from the body to power the system and printable battery systems to store this energy. Together these will result in a self-powered device that will autonomously monitor the electrocardiograph, respiratory flow, oxygen flow and temperature of the patient. This information will then be transmitted wirelessly for online health processing. This real-time self-powered monitoring of a patient's health is currently not available. Thus, the technology that will be developed in SmartVista will position us at the forefront of digital health and wearable biosensor technology for wireless monitoring in hospitals and of remote patients, both of which are necessary in this era of an aging population

Shock-induced aluminum nitride based MEMS energy harvester to power a leadless pacemaker

The next generation of implantable leadless pacemakers will require vibrational energy harvesters in order to increase the lifetime of the pacemaker. This paper reports for the first time the use of a piezoelectric MEMS linear energy harvester device that fits inside a pacemaker capsule. The silicon based MEMS cantilever device uses CMOS compatible Aluminum Nitride as the piezoelectric layer. The developed harvester operates based on a shock-induced vibration that is generated from the low frequency (60–240 beats per minute) high acceleration (>1 g) vibration of the heart. The off-resonance, high g impulses force the high-frequency harvester to oscillate at its resonant frequency. A power density of 97 and 454 μW cm−3 g−2 was achieved for a heart rate of 60 and 240 beats per minute respectively. The forced oscillation causes the linear harvester to dampen after 100–200 ms which reduces the average power compared to a typical sinusoidal excitation. A two and four cantilever system occupies 35% and 70% of the overall volume of the capsule while obtaining 2.98 and 5.96 μW respectively at a heart rate of 60 bpm respectively and 1 g acceleration. The results in this paper demonstrate that a shock-induced linear MEMS harvester can produce enough electrical energy from the vibration of a heart to power a leadless pacemaker while maintaining a small volume

INSPEX: design and integration of a portable/wearable smart spatial exploration system

The INSPEX H2020 project main objective is to integrate automotive-equivalent spatial exploration and obstacle detection functionalities into a portable/wearable multi-sensor, miniaturised, low power device. The INSPEX system will detect and localise in real-time static and mobile obstacles under various environmental conditions in 3D. Potential applications range from safer human navigation in reduced visibility, small robot/drone obstacle avoidance systems to navigation for the visually/mobility impaired, this latter being the primary use-case considered in the project

SARMENTI: Smart multisensor embedded and secure system for soil nutrient and gaseous emission monitoring

Demand for sustainably produced food is driving current strategies for intensification of the agricultural sector worldwide. To meet these challenges farmers will need to adopt a whole-farm approach to resource efficiency. They will increase their productivity with a better application of knowledge per hectare. Optimising soil fertility will enable farmers to maximise their productivity and profitability with higher grass and crop yield and quality

Energy autonomous wearable sensors for smart healthcare: a review

Energy Autonomous Wearable Sensors (EAWS) have attracted a large interest due to their potential to provide reliable measurements and continuous bioelectric signals, which help to reduce health risk factors early on, ongoing assessment for disease prevention, and maintaining optimum, lifelong health quality. This review paper presents recent developments and state-of-the-art research related to three critical elements that enable an EAWS. The first element is wearable sensors, which monitor human body physiological signals and activities. Emphasis is given on explaining different types of transduction mechanisms presented, and emerging materials and fabrication techniques. The second element is the flexible and wearable energy storage device to drive low-power electronics and the software needed for automatic detection of unstable physiological parameters. The third is the flexible and stretchable energy harvesting module to recharge batteries for continuous operation of wearable sensors. We conclude by discussing some of the technical challenges in realizing energy-autonomous wearable sensing technologies and possible solutions for overcoming them

INSPEX: Make environment perception available as a portable system

Obstacle avoidance systems for autonomous vehicles combine multiple sensing technologies (i.e. LiDAR, Radar, Ultrasound and Visual) to detect different types of obstacles across the full range of lighting and weather conditions. Sensor data are fused with vehicle orientation (obtained for instance from an Inertial Measurement Unit and/or compass) and navigation subsystems. Power hungry, they require powerful computational capability, which limits their use to high-end vehicles and robots