Smart lighting in dementia care facility

Ly, Nam Tung; Tscharn, Robert; Preßler, Jan; Huber, Stephan; Aknine, Samir; Serna, Audrey; Hurtienne, Jörn

doi:10.1145/2968219.2968526

Cited by 5 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…With the increasing number of older adults in the world, more technology is needed for elderly care [314]. Some of the applications of these technologies are fall detection, localization, and health status monitoring.…”

Section: ) Elderly Managementmentioning

confidence: 99%

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

et al. 2022

View full text Add to dashboard Cite

Smart lighting has become a universal smart product solution, with global revenues of up to US$5.9 billion by 2021. Six main factors drive the technology: light-emitting diode (LED) lighting, sensors, control, analytics, and intelligence. The Internet of things (IoT) concept with the end device, platform, and application layer plays an essential role in optimizing the advantages of LED lighting in the emergence of smart lighting. The ultimate aim of smart lighting research is to introduce low energy efficiency and high user comfort, where the latter is still in the infancy stage. This paper presents a systematic literature review (SLR) from a bird's eye view covering full-length research topics on smart lighting, including issues, implementation targets, technological solutions, and prospects. In addition to that, this paper also provides a detailed and extensive overview of emerging machine learning techniques as a key solution to overcome complex problems in smart lighting. A comprehensive review of improving user comfort is also presented, such as the methodology and taxonomy of activity recognition as a promising solution and user comfort metrics, including light utilization ratio, unmet comfort ratio, light to comfort ratio, power reduction rate, flickering perception, Kruithof's comfort curve, correlated color temperature, and relative mean square error. Finally, we discuss in-depth open issues and future challenges in increasing user comfort in smart lighting using activity recognition.

show abstract

Section: ) Elderly Managementmentioning

confidence: 99%

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

et al. 2022

View full text Add to dashboard Cite

show abstract

“…De Silva et al (2012) stel ook voor dat kinders só gemonitor kan word om ongelukke te voorkom, terwyl Maras (2015) toestelle noem wat babas kan monitor. Slimhuise kan ook gebruik word om mense se emosionele welstand te verbeter en die slimhuis-ligsisteem, Philips Hue, is reeds in 'n verskeidenheid studies vir hierdie doel gebruik (Capodieci et al, 2018;Clark en Dutta, 2015;Davis et al, 2015;Ly et al, 2016).…”

Section: Soorte Slimhuiseunclassified

’n Bestekopname van slimhuistegnologie vir sekuriteitsdoeleindes in Suid-Afrika

Senekal

2021

Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie

View full text Add to dashboard Cite

Alhoewel slimhuistegnologie sedert die 1970’s bekend is, het dit onlangs in gewildheid toegeneem namate die tegnologie goedkoper en meer gebruikersvriendelik geword het. Digitale assistente, byvoorbeeld Amazon Alexa, Google Assistant en Apple Siri, is ook onlangs by hierdie sisteme geïntegreer, wat verdere toepassingsmoontlikhede geskep het. Die huidige studie ondersoek die potensiaal van hedendaagse slimhuistegnologie om mense se veiligheid te verbeter. Beheerstelsels soos Amazon Echo, Google Nest en Apple Homekit word bespreek, tesame met toegewyde slimhuis-sekuriteitstelsels soos Ajax en Hikvision AX PRO. Radioprotokolle en sommige sensors word ook ondersoek, met ’n spesifieke klem op hulle vermoëns en gebreke. Laastens word ’n aanbeveling gemaak en ’n voorbeeld van ’n toepassing vir veiligheidsdoeleindes word in Apple se Homekit met behulp van Apple se Shortcuts saamgestel.

show abstract

“…Existing studies in this context primarily focused on developing ubiquitous systems for supporting people living with cognitive impairments [5]- [7]. Although few works in the literature have focused on early detection of cognitive impairments, they primarily analyze specific activity patterns monitored through specialized sensors [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

CogAx: Early Assessment of Cognitive and Functional Impairment from Accelerometry

Ramamurthy

Chatterjee

Galik

et al. 2022

2022 IEEE International Conference on Pervasive Computing and Communications (PerCom)

View full text Add to dashboard Cite

An individual's cognitive and functional abilities are commonly assessed through physical and mental status examination, observational performance measures, surveys and proxy reports of symptoms. These strategies are not ideal for early impairment detection as the individual needs to be present physically at the clinic to avail the assessments, especially for older adults who require assistance from a caregiver, and experience mobility, cognitive and functional disabilities from neurodegenerative disorders. Moreover, these strategies rely on self-reporting and proxy reports for evaluation which often leads to under-reporting of symptoms and decrease the validity of these measures. We argue that an early assessment of functional, and cognitive health impairment can be obtained from the individual's daily activities captured through accelerometry. In this work, we postulate to learn high-level motion related representations from accelerometer data to better correlate with underlying functional and cognitive health parameters of older adults using a contrastive and multi-task learning framework. In particular, we posit a novel indicator, Impairment Indicator using the proposed multi-task learning framework that can indicate functional or cognitive decline as neurodegenerative disease progresses. An extensive 24-hour data collection from 25 older adults with the clinician in-the-loop was carried out in a retirement community center with IRB approval. We collected the activity patterns using wearables in their homes in addition to survey-based assessments and observational performance measures recorded by a clinical evaluator to infer their current cognitive and functional impairment status. Our evaluation on the acquired dataset reveals that the representations learned using contrastive learning aids in improving the detection of activities, activity performance score, and stage of dementia to 92%, 97%, and 98%, respectively.

show abstract

Smart lighting in dementia care facility

Cited by 5 publications

References 5 publications

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey

’n Bestekopname van slimhuistegnologie vir sekuriteitsdoeleindes in Suid-Afrika

CogAx: Early Assessment of Cognitive and Functional Impairment from Accelerometry

Contact Info

Product

Resources

About