Poor sleep quality and pattenr causes several health problems and sleep disturbances increase the risk of falling.

However, no studies developed a model to explain how poor sleep quality increases the risk of falling while rising-up from a bed or chair, which account for up to 30% of in-door accidental falls.

This study prelimnary explroed for the first time associations between Sleep quality & Centre-of-Pressure sway in order to develop mathematical models to assess the risk of falling.

In particular, this grant supported the acquisition of a state of the art wearable monitor for monitoring physiological signals (i.e. EEG, ECG, EOG, EMG, SpO2, GSR, Actigraphy).

This Summer School spoke directly to Warwick PhD students, early career researchers and academics with a technical background (i.e. physics, chemistry and/or engineering), who were working on healthcare technologies, and aimed to provide them with theoretical and practical multidisciplinary training on HTA principles.

This will included methodology, modelling, mathematics, laboratory based training and relevant case studies (i.e. medical devices and not only drugs). The learned principles, methods and tools that have been important to inform their activities, maximizing the uptake and impact of their research outcomes. In fact, informing the research and the design of new healthcare technologies with scientific methods for early stage HTA will have a considerable impact on a number of important elements (i.e. cost-effectiveness, ethical issues) during the research process, when with small changes it is possible to achieved big results.

This School was organised in Collaboration with:

• the Institute of Advanced Study (IAS), University of Warwick

• the School of Engineering, University of Warwick

• the Global Research Priority on Science and Technology for Health, University of Warwick

• the HTA Division of the International Federation of Medical and Biological Engineering (IFMBE)

• the Institute of Biomedical Technology, Patras, Greece.

• the COST Action BM1309 “European network for innovative uses of EMFs in biomedical applications”.

Moreover, the school has been endorsed by:

• the European Alliance for Medical and Biological Engineering (EAMBES)
• the COST action TD1104 “European network for development of electroporation-based technologies and treatments”
• the COST action TD1301 “Development of a European-based Collaborative Network to Accelerate Technological, Clinical and Commercialisation Progress in the Area of Medical Microwave Imaging”

The Goal of this project was to develop of a mathematical model for the prediction of orthostatic hypotension by monitoring indirectly those states of Autonomous Nervous System (ANS) and Cardiovascular System (CVS) that are responsible for homeostasis of blood pressure.
The main outcomes of this project have been:

Invited talks:

• 2016, Invited talk, Leandro Pecchia, “Does Heart Rate Variability (HRV) serve as a potential fall risk factor in the elderly?”, European College of Sport Science (ECSS2016), 6th-9th July 2016, Vienna, Austria
• 2015, Keynote talk, Leandro Pecchia, “Physiological monitoring and biomedical signal processing for fall prediction in elderly”, World Congress on Medical Physics and Biomedical Engineering, June 7-12, 2015, Toronto, Canada.

Publications:

• Sannino G, Melillo P, De Pietro G, Stranges S, Pecchia L, (2015) “Short term heart rate variability to predict blood pressure drops due to standing: a pilot study”, BMC Medical Informatics and Decision Making, 2015, 15(S3):S2 doi:10.1186/1472-6947-15-S3-S2
• Melillo P, Jovic A, De Luca N and Pecchia L (2015) "An automatic classifier based on heart rate variability to identify fallers among hypertensive subjects", IET Healthcare Technology Letters, 2 (4): p 89-94, DOI: 10.1049/htl.2015.0012
• Sannino G, Melillo P, De Pietro G, Stranges S, Pecchia L, (2015) "Blood Pressure Drop Prediction by using HRV measurements in Orthostatic Hypotension", Journal of Medical Systems, 39(11):292 DOI: 10.1007/s10916-015-0292-5

Patents:

• PCT application number PCT/GB2015/052581 and No RM2014A000504, title “Method to predict falls”, status “pending”, authors: L Pecchia, S Stranges, P Melillo, G De Pietro, G Sannino, filed the 5^th of September 2014.