Page 253 - Handbook of Electronic Assistive Technology

242 HANDBOOK OF ELECTRONIC ASSISTIVE TECHNOLOGY

Lifestyle Monitoring

There have been developments in lifestyle monitoring systems (LMS), which is the use
of technology for monitoring movements of a person around the living space. Lifestyle
monitors track the time that movements occur and can be used to assist in deter-
mining when a person gets up in the night or has behaviour out of the ordinary. The
only project which attempted lifestyle monitoring, described previously, was the BT/
Anchor project and this reported a high number of false alerts (45 out of 61). Based on
a 2-week training set, the House_n group at the Massachusetts Institute of Technology
concluded that while the model’s accuracy for some activities is better than chance,
it is not as high as expected (Tapia et al., 2004), while an evaluation of a four-person
family for a year found that 17 out of 73 unusual states coincide with real-life changes
in habitual behaviour (Matsuoka, 2004). A study by Brownsell et al. (2008) reported
that lifestyle monitoring requires further development, and another by Hanson and
Osipovic (2007) suggested that retrospective interpretation requires large amounts of
contextual information and that there are technical and operational difficulties to be
resolved before it will be possible to use LMS predicatively. The use of sophisticated
analysis methods has been applied to the problem, such as spatial/temporal reasoning,
temporal granularity and causal reasoning (Augusto and Nugent, 2006), but accurate
prediction of activity remains elusive despite some encouraging results (Suryadevra
and Mukhopadhay, 2012).
The evidence suggests that LMS will take some time to mature and that large data
sets will be required to support effective implementation. Given that a significant
amount of baseline data will be required to effectively monitor someone who has
been identified at some risk, the implementation of LMS will obviously benefit from a
preexisting infrastructure where data might already be continually collected and col-
lated. One can envisage a smart house system incorporating a temporary data buffer,
capable of holding a number of weeks of activity data, which is only ‘activated’ and
accessed if required to support an LMS requirement. This, along with intelligent energy
management, makes another argument for general implementation of home smart
technologies.

Carer Support

For individuals who have significant, complex needs, such as those with learning disabil-
ity and challenging behaviour, the relationship of the individual to their environment and
those around them can be complex (Felce et al., 2013). Legislation underpins the gen-
eral policy move to social inclusion and expression of individual rights (Parkin, 2016).
Providing care in such circumstances, that is, maintaining dignity and developing inte-
gration into a social context, while providing safety and security for the individual and
those around them within limited budgets, presents specific challenges that technology
is now being routinely asked to address. The complexities associated with creating and