Abstract of paper that was presented at The 12th National Conference of Emerging Researchers in Ageing

Ghahramani, Maryam

Naghdy, Fazel

Naghdy, Golshah

Potter, Jan

Stirling, David

English

Research Online

University of Wollongong Research Online Faculty of Engineering and Information Sciences - Papers: Part A Faculty of Engineering and Information Sciences 1-1-2013 Fall risk assessment in older people using inertial sensors Maryam Ghahramani University of Wollongong, mg846@uowmail.edu.au Fazel Naghdy University of Wollongong, fazel@uow.edu.au David Stirling University of Wollongong, stirling@uow.edu.au Golshah Naghdy University of Wollongong, golshah@uow.edu.au Jan Potter University of Wollongong, janp@uow.edu.au Follow this and additional works at: https://ro.uow.edu.au/eispapers  Part of the Engineering Commons, and the Science and Technology Studies Commons Recommended Citation Ghahramani, Maryam; Naghdy, Fazel; Stirling, David; Naghdy, Golshah; and Potter, Jan, "Fall risk assessment in older people using inertial sensors" (2013). Faculty of Engineering and Information Sciences - Papers: Part A. 2128. https://ro.uow.edu.au/eispapers/2128 Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: research-pubs@uow.edu.au Fall risk assessment in older people using inertial sensors Abstract Abstract of paper that was presented at The 12th National Conference of Emerging Researchers in Ageing. Keywords assessment, older, people, sensors, inertial, fall, risk Disciplines Engineering | Science and Technology Studies Publication Details M. Ghahramani, F. Naghdy, D. Stirling, G. Naghdy & J. Potter, "Fall risk assessment in older people using inertial sensors," in Enabling Active Ageing Conference Proceedings: The 12th National Conference of Emerging Researchers in Ageing, 2013, pp. 56-56. This conference paper is available at Research Online: https://ro.uow.edu.au/eispapers/2128 56  FAMILY MEMBER EXPERIENCES DURING AN OLDER LOVED ONE’S DELIRIUM DAY Jenny1, HIGGINS Isabel1, KEATINGE Diana1 1University of Newcastle The research described in this poster explores the lived experience of family members who are with their older loved one during delirium. Based on phenomenology the study is concerned with describing the meanings of family member experiences during delirium  in older people. Understanding the experiences of family members  is  important for the provision of  support  to  family members and  the appropriate  involvement of  family members  in  the older person’s care.  The  importance  of  healthcare  staff  and  services  regarding  family members  as  integral  to  quality  care  and supporting  them  is highlighted  in contemporary  literature. Despite  this acknowledgement, the experience, role and concerns  of  family members  are  often  unknown  or  overlooked  during  the  care  of  older  people.  Family  support strategies  have  been  suggested  by  some  authors  however  there  has  been  little  exploration  of  family  member experiences during delirium as a basis for these strategies, highlighting the importance of this study. The preliminary findings  of  the  study  are  presented  in  the  poster.  Changing  family  portraits:  Sudden  existential  absence  during delirium depicts family member experiences of being with their older  loved one during delirium. Existential absence for  family members  is experienced as suddenly  losing the  familiar presence of their  loved one as a person, and the arrival  of  a  stranger’s  presence.  These  findings  have  the  potential  to  increase  recognition  of  the  impact  of  older person delirium on  family members,  to  increase  recognition of  the  family within  comprehensive  care of  the older person in the Australian healthcare system, and to inform further research related to family support and involvement in care during delirium. The study supports active ageing by understanding the impact of delirium on family members, often people who are older themselves, and suggesting the support they need to maintain wellbeing.  FALL RISK ASSESSMENT IN OLDER PEOPLE USING INERTIAL SENSORS GHAHRAMANI Maryam ¹, NAGHDY Fazel ¹, STIRLING David ¹, NAGHDY Golshah ¹, POTTER Jan² ¹School of Electrical, Computer and Telecommunications Engineering, University of Wollongong   ²Illawara Health and Medical Research Institute, University of Wollongong Almost 30% of people above 65 years of age fall each year all over the world. This figure increases to 40% for people older than 80. Falls have the highest percentage of injury‐related deaths and fall related injuries have the highest cost after vehicle injuries. The mortality rate of fall increases dramatically with age and 70% of accidental deaths in persons above 75  are  caused by  fall.  Fall  in older people have many  severe  outcomes.  Fall  is  the  cause of 10% of elderly rushing to the hospitals and 6% of further hospitalization. The fall consequences can be physical such as fractures, as well as social such as isolation and depression. It is proved that frail elderly fallers display a significantly slower walking speed than non‐fallers. Gait is a complex motor phenomenon with many other measurable facets besides speed that might  identify  fall  risk. Walking  speed,  cadence,  stride  length  and  stride  time  are  important  factors  which  are significantly different between fallers and non‐fallers. In addition, balance plays a key role  in fall prediction. Keeping balance, an automatic process  in healthy people, can be challenging  for the elderly while doing daily chores.  In this study,  an  objective method  to  assess  the  fall  of  risk  in  older  people  using  inertial  sensors  is  proposed.  The  data deployed  in  the  study  is  obtained  through MTw Development  Kit  from  Xsens  technology. MTw  is  a  small,  highly accurate wireless  inertial 3D motion  tracker  consisting of 6  inertial  sensors. MTw has many benefits  compared  to similar  inertial sensors. MTw kit  is completely wireless and portable which makes  it very practical and easy  to use. Data  is collected  in  the Windows  software package MT Manager. This  software allows configuration of  the MTw’s, real‐time view of 3D orientation and sensor data,  recording of data streamed  from  the MTw’s  through  the Awinda Station and export to ASCII files for further analysis. The kinematic data is subsequently used, using an intermediate program coded in MATLAB. Using the data, a stochastic method, based on Gaussian Mixture Model is used to identify deviation from normal gait. The results obtained so far indicate that the proposed method can assess the risk of fall caused by aging.

Fall risk assessment in older people using inertial sensors

https://ro.uow.edu.au/cgi/viewcontent.cgi?article=3137&amp;context=eispapers

Fall risk assessment in older people using inertial sensors

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