A new range of outdoor clothing for the active ageing based on wearable technologies
Submitting Institution
University of UlsterUnit of Assessment
Computer Science and InformaticsSummary Impact Type
TechnologicalResearch Subject Area(s)
Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Cardiorespiratory Medicine and Haematology, Neurosciences
Summary of the impact
Two leading manufacturers of clothing for outdoor activities ([text
removed for publication]) have produced a new range of functional clothing
based on research at Ulster on wearable technologies for the active
ageing. The new age-appropriate outdoor garments incorporate wearable
technologies that enable self-monitoring of physiological parameters
(heart rate, respiration rate) and activity levels (step-counts, distance
walked) with optimal placement of sensors to improve signal-to-noise
ratio. Additionally, [text removed for publication], a company producing
[text removed for publication], have used feedback from Ulster's research
evaluations to design a new range of [text removed for publication] that
are incorporated into the garments, achieving increased levels of
usability by elderly people.
Underpinning research
In modern healthcare services, a growing emphasis is being placed on
self-awareness and self-management of health and wellbeing, particularly
amongst the increasing number of older but active members of the
population. At the centre of this paradigm is a new range of biophysical
monitoring devices (e.g. heart rate monitors, step-counters). For such
devices to be most effective, significant challenges exist about where and
how to best locate them on the body. Sub-optimal placement of the
biophysical monitoring devices leads to significant loss in accuracy of
the measurements processed from the data acquired, thus rendering the
devices less effective for self-monitoring.
Processing and classification of physiological signals has been a core
area of research at Ulster for over 15 years. Results of our research in
electrocardiology have demonstrated that appropriate combination of
feature selection techniques in conjunction with bi-group classification
models improves the classification of the 12-lead ECG [1]. The knowledge
gained through this research has been extended through the classification
of entire body surface potential maps (192 electrode arrays) (2003-2007).
Electrode arrays were initially processed to reduce their dimensionality
prior to classification [2]. This research stimulated the hypothesis that
a reduced set of electrodes from the body surface map could be used to
improve classification performance compared with both the 12-lead ECG and
the full body surface map. Our research also considered the restrictive
nature of connecting electrodes/cables to human subjects and the
impracticalities of this for long-term monitoring [3]. Subsequently,
textile-based electrodes have shown promise for the measurement of the
ECG, as they do not require a gel membrane or adhesive, and are thus
better suited to long-term monitoring applications. Furthermore, clothing
enables textile sensors to be placed in close physical proximity to a
large area of the body.
Research on optimal configuration and positioning of electrodes within a
range of wearable applications has been undertaken [3] (2008-2013). Data
mining approaches were shown to be capable of identifying an optimal set
of 10 electrodes that yield accuracy of signal measurement similar to that
achieved using the entire 192 electrode array. The results from this work
formed the basis of the technology work-package in the Design for Ageing
Well (DFAW) project, funded by the ESRC New Dynamics of Ageing programme.
Within DFAW (2009-2012) the effects of positioning sensors in different
locations within clothing for the active ageing were investigated. The
effects on the accuracy of both activity recognition and step-count
measurement were considered [4, 5]. Findings from this research show the
hip to be the optimal location for sensor placement, and that no
significant improvement is achieved in the accuracy with which activity
levels are detected by using configurations of two or more sensors [6].
User evaluations with walking groups provided insights into the manner in
which the feedback on wearable devices should be provided and how the
garments should be designed to incorporate the technological components to
maximise ease of operation.
This work has been conducted by a team of key researchers in CSRI:
Chris Nugent |
Professor of Biomedical Engineering (joined as
Lecturer, 05/2000) |
Dr Dewar |
Finlay Research Associate/Lecturer/Senior Lecturer
(06/2000-present) |
Dr Paul McCullagh |
Lecturer/Senior Lecturer/Reader (01/1993-present) |
Sally McClean |
Professor of Mathematics (joined as Research Assistant,
1971) |
Bryan Scotney |
Professor of Informatics (joined as Lecturer, 1984) |
Dr Mark Donnelly |
PhD student/Research Associate/Lecturer (10/2004-present) |
Dr Ian Cleland |
PhD student/Research Associate (10/2009-present) |
Mr Liam Burns |
Research Associate (08/2007-present) |
References to the research
* References that best indicate the quality of the underpinning
research.
[1] * CD Nugent, JAC Webb, ND Black, GTH Wright, M McIntyre (1999). An
Intelligent Framework for the Classification of the 12-lead ECG, Artificial
Intelligence in Medicine, vol. 16, no. 3, pp. 205-222.
http://www.aiimjournal.com/article/S0933-3657(99)00006-8/abstract
[This paper was included as an output in Ulster's RAE 2001
submission for (then) UoA25, Computer Science.]
[2] * MP Donnelly, CD Nugent, D Finlay, NF Rooney, ND Black (2006).
Diagnosing Old MI by Searching for a Linear Boundary in the Space of
Principal Components, IEEE Transactions on Information Technology in
Biomedicine, vol. 10, no. 3, pp. 476-483.
DOI: 10.1109/TITB.2006.876033
[This paper was included as an output in Ulster's RAE 2008
submission for (then) UoA23, Computer Science & Informatics, in
which 94.9% of outputs were judged to be 2* or better.]
[3] * DD Finlay, CD Nugent, MP Donnelly, PJ McCullagh, ND Black (2008).
Optimal Electro-cardiographic Lead Systems: Practical Scenarios in Smart
Clothing and Wearable Health Systems, IEEE Transactions on Information
Technology in Biomedicine, vol. 12, no. 4, pp. 433-441
DOI: 10.1109/TITB.2007.896882
[This paper was included (as a then internet publication) as an
output in Ulster's RAE 2008 submission for (then) UoA23, Computer
Science & Informatics, in which 94.9% of outputs were judged to be
2* or better.]
[4] S Zhang, P McCullagh, CD Nugent, H Zheng, M Baumgarten (2011).
Optimal Model Selection for Posture Recognition in Home-based Healthcare,
International Journal of Machine Learning and Cybernetics, vol. 2,
no. 1, pp. 1-14.
DOI: 10.1007/s13042-010-0009-5
[5] I Cleland, CD Nugent, D Finlay, W Burns, J Bougourd, R Armitage
(2012). Effects of Accelerometer Coupling on Step Count Accuracy in
Healthy Older Adults, Health and Technology, vol. 2, no. 4, pp.
259-270.
DOI: 10.1007/s12553-012-0036-1
[6] I Cleland, B Kikhia, CD Nugent, A Boytsov, J Hallberg, K Synnes, SI
McClean, D Finlay (2013). Optimal Placement of Accelerometers for the
Detection of Everyday Activities, Sensors, vol. 13, pp. 9183-9200.
DOI: 10.3390/s130709183
Key Grants
Project: Design for Ageing Well: Improving the Quality of Life for
the Ageing Population using a Technology-enabled Garment System
Funder: ESRC New Dynamics of Ageing (RES-353-25-004) £193,895 (to Ulster)
Dates: 09/2008-09/2011
Ulster grant-holders: CD Nugent, D Finlay, P McCullagh, SI McClean, BW
Scotney
Project: Design for Ageing Well: PhD Studentship
Funder: ESRC New Dynamics of Ageing (RES-353-25-004) £51,301 (to Ulster)
Dates: 10/2009-10/2012
Ulster grant-holders: CD Nugent, D Finlay, P McCullagh, SI McClean, BW
Scotney
Project: Cross-border Centre for Intelligent Point-of-Care Sensors
Funder: NI Department of Employment and Learning £1,991,283 (to Ulster)
Dates: 11/2008-03/2011
Ulster grant-holders: CD Nugent, D Finlay, P McCullagh, SI McClean, BW
Scotney
Details of the impact
[text removed for publication] and [text removed for publication] have
both produced a new range of functional clothing for the active ageing
based on research by CSRI and the DFAW project. In addition, [text removed
for publication] has been guided by CSRI's research in the re-design of
their [text removed for publication] product [text removed for
publication] to facilitate integration within functional clothing for use
by the active ageing.
Results from CSRI's research conducted within DFAW [E1] have been used by
the wearable technology providers [text removed for publication] and [text
removed for publication] [E2]. [text removed for publication] have
improved their knowledge of electrode positioning for physiological
monitoring [3, 5] (2008-2012). [text removed for publication] have used
CSRI's research, and analysis of feedback from the user group of active
older persons in DFAW, to reconfigure the [text removed for publication]
in their [text removed for publication] product to control mobile-based
applications and to redesign the switch component "to improve the size and
positioning of the [text removed for publication] (to allow) for the
reduced dexterity of older users" (2008-2012) [E2].
The co-design process, one of the central results from DFAW [E1]
(2008-2012), was used as a methodology to produce a range of
age-appropriate clothing with integrated technologies. These garments were
demonstrated at [text removed for publication] in a joint exhibition with
[text removed for publication] [E1]. [text removed for publication] have
incorporated the research results into their current range of clothing
relating to age-appropriate shape and fit, styling and fabric selection.
The recommendations from DFAW have also guided [text removed for
publication] in the design of the garment layering system as a basis for
incorporating wearable electronics [E3]. These recommendations relate to
CSRI's research findings for the most appropriate positioning of sensor
and control technologies within the garments in order to both maximise
usability from an active ageing perspective and to improve the accuracy of
the physiological measurements processed from the data acquired by the
sensors (ECG, and measurements of levels of activity) [4, 5, 6].
[text removed for publication], a niche outdoor clothing manufacturer,
have adapted their manufacturing procedures to support the incorporation
of technology within smart garments [E4] (2012) in relation to the optimal
positioning of the technology and how the technology is encapsulated
within the garment during the assembly process. This change in
manufacturing practice is based on [text removed for publication]
involvement in DFAW, particularly the garment manufacturing methodology
produced by the project and [text removed for publication] experience of
working with DFAW's multidisciplinary research team in the production of
prototype garments. A feature presented by [text removed for publication]
during 2012 demonstrated how the manufacturing process had been adapted
within [text removed for publication] and how the company was now able to
incorporate wearable technologies from DFAW into their garments [E5].
Engagement with users from walking groups has resulted in a series of
testimonials that report the positive experiences of active older persons
who have used the new clothing for outdoor activities. A 70-year-old
participant in the evaluations, who reported that she enjoyed walking as
part of an active life, stated that her involvement in DFAW has resulted
in her being "more inclined to go out and exercise" and that she was now
"more aware of the options" available for technology-enabled
age-appropriate clothing [E6]. A 67-year-old male who was a member of a
walking group reported that in his opinion the use of age-appropriate
clothing (as evaluated as part of DFAW) would make people "more likely to
become involved in recreational activities" [E6].
The research expertise developed by CSRI in wearable technologies [3, 5,
6] is further recognised through influencing definitions of new
terminology that are used in standards within the textile industry. The
Textile Institute, a worldwide organisation for textiles, clothing and
footwear, recognised the importance of "smart textiles". In revising their
publication "Textile Terms and Definitions" (TT&D) in 2012, the
Institute wished to reflect the importance of the emerging "smart textile"
sector through its inclusion in the revised version [E8]. In 2012 Prof
Nugent was invited by the Textile Institute to join a committee of 12
international experts from the smart textiles community, from both
academia and industry, to assist in the revision of the TT&D
publication [E9]. (Nugent was one of two technology expert members on the
committee.) The output from the committee is a new set of terms and
definitions relating to smart textiles from design, technology and
clothing perspectives that were not addressed previously in the Textile
Institute's TT&D publication.
This work can be associated in part with a collaboration with Professor
Jane McCann (University of South Wales, Newport), project co-ordinator of
the DFAW project. CSRI were the technology co- ordinators of the DFAW
consortium, and the work on incorporating wearable technologies into smart
garments for the active ageing was conducted by CSRI. Subsequently ESRC
has indicated that they wish to highlight the results from the DFAW
project as one of their selected Impact Case Studies [E1, E9].
Sources to corroborate the impact
[E1] Publication by the NDA (New Dynamics of Ageing) Research Programme
showing results from the Design for Ageing Well project.
This item provides corroborating evidence of the positive impact
experienced by older persons when using the wearable technologies that
have been designed for active ageing. The item contains information about
the joint expo with [text removed for publication].
[E2] Factual Statement in the form of a letter from [text removed for
publication].
This item provides corroborating evidence that results from the Design for
Ageing Well project have been used to inform the redesign of their [text
removed for publication] product for ageing users.
[E3] Factual Statement in the form of a letter from [text removed for
publication].
This item provides corroborating evidence that results from the Design for
Ageing Well project have influenced the range of clothing development that
has already been prototyped and shown at the [text removed for
publication].
[E4] Factual Statement in the form of a letter from [text removed for
publication].
This item provides corroborating evidence that the Design for Ageing Well
project has informed the manufacturing process of clothing lines to
incorporate wearable technologies.
[E5] Feature on [text removed for publication] during March 2012.
This item provides corroborating evidence of the impact of our research on
[text removed for publication], informing change that is required in the
manufacturig process for wearable technologies.
[E6] End-user testimonials.
These items provide corroborating evidence of detailed feedback from users
from a walking group who have evaluated the wearable technology and have
had positive experiences when using it.
[E7] A letter from the Textile Institute.
This item provides corroborating evidence that the textile industry
recognise the need to consider smart textiles as a new domain and the need
to define new terms and definitions for Smart Garments.
[E8] Letter of invitation to Prof. Chris Nugent from the Textile
Institute to join their new Committee on "Smart Textiles".
This item provides corroborating evidence of the recognition of transfer
of knowledge from CSRI to production of guidelines for the Textile
Institute.
[E9] Corroborating contact: Director of the New Dynamics of Ageing
programme.
This person is knowledgeable about the programme of work carried out by
CSRI in the ESRC-funded Design for Ageing Well project, including our
engagement with the textile industry and with user groups, the overall
findings of the project, and the resulting impact on development and
production of new technology-enabled garments for the active ageing
population.