Mohsen Amiribesheli: Adapted Home Environments for People with Dementia

Researcher: Mohsen Amiribesheli

Mohsen  joined the faculty of Science and Technology in September 2013 as a full time PhD student. He received his MSc in computing at the University of Dundee with the thesis titled “Investigating and studying diverse visualization methods on different platform’s base on a stakeholder specific Tele-care system” in 2012.  He has been involved in a number of research projects in the field of Computer networking, Human Computer Interaction (HCI) and Data mining. Mohsen also received a number of certificates from Microsoft and Cisco and has been involved in many  implementation projects.

Email Mohsen Amiribesheli here, Staff Page.

A research of the Smart Technology Research Centre (STRC).

Research project: Adapted Home Environments for People with Dementia

Dementia is one of the most common causes of mortality in older people. Health care systems around the world are under immense pressure from the growing costs of continuous care for older people with dementia. A relatively effective solution to this problem is to shift the emphasis from formal cares in hospitals and care homes, to informal care in the home.

Smart Home (SH) technologies, as an instance of Ambient Assisted Living (AAL), consist of a mix of technology components (e.g., sensors, actuators, software, etc.)  to support its resident to live more independently with better quality of life. SH technology has been proposed to reduce the living and care costs and to improve the quality of life for elder populations with dementia. AAL technologies are diverse and versatile: video monitoring, health monitoring, fall detection, hip protector, light management, smart smoke alarm, smart fire alarm, movement detector, smart security alarm, kitchen monitor system, smart planners and calendars, drug time reminder, etc. Monitoring the daily activity of patients with dementia enables to control the environment on behalf of the residents and predicts their future behaviour. It also enables to track their health situation (tele-health).

How will this PhD research contribute to the knowledge of its field?

Informal care for a patient with chronic, progressive diseases such as dementia could be immensely expensive and complicated. In the past few decades, researchers tried to cut the care costs and make it more affordable and less intrusive by introducing intelligent assistive technologies and intelligent environments (ambient intelligent).

In this research the proposed activity recognition methods empowers the data processing layer of the Smart Home (SH) to benefit from the state of the art algorithms and methods (e.g., sensor modality for activity recognition) to to design a monitoring and emergency detection system for people with dementia. The final prototype of this PhD is a functional SH platform which processes the sensor data collected from an elderly person in a smart home, recognizes the daily activities of the resident, finds anomalies in the resident’s behaviour over time and provides assistance in risky situations.

The main contributions of this research will be discovering solutions to problems around areas such as, accuracy and methods to define abnormal (risky) and normal behaviours for the system, considering aspects such as reliability and level of intrusiveness to resident’s private life. Academic publications will be the main way to disseminate the findings of the research.

This PhD research tries to give answers to questions such as:

  • What is the realistic picture of the current state of the art SH technologies?
  • What are stakeholders’ needs and to-do list for the system (considering must have and good to have from requirement analysis stage)?
  • How can the system integrate warning, reminding and monitoring functionalities?
  • How can a real-time monitoring system adapt to dynamically changing environments be developed for dementia patients?
  • What are the richest, the most reflective and the most feasible real life ADL scenarios and how the quality of life of patients on those scenarios can be improved by the proposed SH?
  • What is the most suitable type of activity recognition method for analysing the collected scenario?
  • What visualisation technique can be used to present anomalies and behavioural patterns more clearly?
  • What triggers should be associated with different risky situation in the context of older people with dementia who live independently?
  • What are the current and future challenges of SH for people with dementia from the aspects such design factors and system’s acceptability?

Supervisory Team of the Project

Dr Abdelhamid Bouchachia, Dr Hammadi Nait-Charif and Dr Emilio Balaguer-Ballester.