Chris Bowers

How we move = how we feel

How we move = how we feel. Therefore, if we change the way we move, then we can change how we feel.

This is the core idea that Dance Movement Psychotherapy is built upon.

If we now look at the workforce in the UK, we find that 12.5 million working days were lost in the UK due to stress (Health and Safety Executive, 2017). Many people work sedentary, where very little movement takes place. So with the above core idea, if we get the workforce moving we should be able to change the way they feel, which has been found to work – problem is – any engagement with movement practices (yoga, walking etc) takes time away from the desk and actually doing work.

This project involves developing a programme that is integrated into the working day for those who spend most of their day at a computer. The programme will be built with movement theories, developed by Rudolf Laban, in mind and will measure the impact the programme has on well-being.

This project will be undertaken in collaboration with Gillian Hipp who is undertaking a PhD in this area.

 

Supervisor

Reducing Sedentary Behaviour Amongst Gamers

sedentary gamer

The project will address the issue of excess sedentary behaviours typically undertaken by gamers. The project may consists of the following:

 - Undertake a critical literature review of sedentary behaviour interventions and examine their effectiveness
 - Develop a novel technology driven sedentary behaviour intervention on gamers.
 - Evaluate the effectiveness of this newly developed intervention.
 

Supervisor

Automatic Detection of Emerging Social Media Trends

The project will use simple Computational Intelligence techniques to automatically detect emerging trends on Twitter.

New trends are often identifiable by: 
 - Density of tweets/retweets sharing hashtags
 - Novelty of hashtag

The resulting application should identify any tweets that belong to an emerging trend and present them to the user. 

Supervisor

Exploiting QR codes using an Evolutionary Algorithm

qr code example

This project will investigate the feasibility of using Evolutionary Computation to generate QR codes which contain aesthetically appealing patterns or shapes. 

QR codes typically appear to contain a random black and white grid of squares. However this pattern is carefully crafted to ensure that a URL can be encoded in a robust fashion. Its therefore very difficult to create a QR code with a desirable pattern or structure.

This project will attempt to create QR codes that contain patterns of black and white squares that form an identifiable pattern or shape that is aesthetically appealing. The resulting QR codes may have a significant commercial value as compared to apparently randomly generated codes.

Supervisor

Indoor position sensor

A mobile device is capable of determining its position to an accuracy of up to 10 meters when outdoors. However indoor position requires a greater degree of accuracy to be useful (<1m) and is hampered by lack of GPS line of sight. 

This project will investigate the use of a variety of sensors in combination (Magnetic field, Bluetooth, GPS, WiFi, orientation) to create a virtual sensor which estimates indoor position. This approach will utilise a technique known as sensor fusion (https://en.wikipedia.org/wiki/Sensor_fusion).

Supervisor

Detecting Physical Misuse of Mobile Devices

damaged phone

Due to the ubiquitous and pervasive nature of mobile devices they are prone to being exposed to a wide variety of potentially hazardous environments and situations. There is a growing interest in being able to monitor and detect exposure to such environments. An example of this is the inclusion of water ingress detectors in many mobile devices that change colour when exposed to water. 

This project aims to extend the kinds of hazards that can be detected by mobile devices. In particular it should look at impact forces and generate notifications of potentially harmful forces. The project would consist of development and evaluation of potential detection techniques using existing sensors and to develop a working prototype logging and notification application.

Supervisor