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Towards an ontology-based system to foster Older Adults’ Mental health via Indoor Comfort management

Promoting Healthy Aging through Semantic Enrichment of Solitude Research (PHASES) – JOWO 2025

Sep. 9th, 2025

Daniele Spoladore, Anđela Đinđić, Walter Terkaj

National Research Council of Italy (CNR)

FOIS 8-9 Sept. – JOWO 8-9 Sept. 2025, Catania (Italy)

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Presenter

Daniele Spoladore

  • Researcher at the Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing – Cnr, Lecco premises
  • PhD in Computer Science from the Insubria University (2022)
  • Research activity: ontology engineering and its methodology, application of ontologies to the medical, rehabilitation, and Ambient Assisted Living domains

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Table of contents

  1. Context & Research question
  2. The Older Adults Indoor Comfort (OAIC) ontology engineering process
    • Domain analysis: OAs, mental health & indoor comfort
    • Conceptualization
    • Development
  3. Use cases
  4. Future works

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Context – Ageing population

  • Greying of Europe
  • Older Adults (OAs) number is increasing
  • Ageing ⇒ chronic physical and mental conditions, disability
  • Aged ≥85 ⇒ systematic physical and cognitive impairments

65+ years old ~ 25% population

80+ years old ~ 8% population

Istat, 2023

Eurostat, 2023

65+ years old ~ 21% population

80+ years old ~ 6% population

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Context – Active Aging and AAL

  • MEDICAL & SOCIAL PERSPECTIVE: WHO Active Ageing Framework 🡪 multidimensional and holistic approach

  • TECHNOLOGICAL PERSPECTIVE: Ambient Assisted Living (AAL) 🡪 technological paradigm to support OAs’ independent living – particularly in Activities of Daily Living

Source: WHO

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Context – IEQ

  • AAL solutions often support OA in coping with their impairments (particularly in ADLs)
  • AAL solutions have the potential to manage indoor environmental quality (IEQ) by intervening on indoor comfort metrics
  • IEQ plays a pivotal role in human health and wellbeing
    • Air quality and pollutants 🡪 impairments of the respiratory system
    • Temperature 🡪 impairments of the cardiovascular system
    • Light 🡪 impairments of the vision
    • Noise 🡪 cognitive and hearing impairments

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Research Question & Methods

  • Research question:

Can AAL systems support emotional wellbeing by managing IEQ?

    • What are the determinant factors of OAs’ emotional wellbeing?
    • What are the correlations between OAs’ mental issues and IEQ?
  • Methods:

Developing an ontology-based framework for the management of IEQ f for OAs living autonomously

    • Collaborative ontology engineering process
    • Use cases & inference validation

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OAIC ontology engineering process

  • Agile, Simplified and Collaborative Ontology engineering methodology (AgiSCOnt)
  • Iterative collaboration in decentralized contexts with several domain experts
  • Domain experts:
    • 2 psychologists
    • 2 biomedical engineers
    • 2 gerontologists
    • 3 architects and designers
    • 2 computer scientists

Source: 10.1016/j.compind.2023.103979

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OAs, mental health & IEQ

  • 14% OAs in the world live with a mental disorder
  • 27.2% of suicides in the world happen in people aged >60
  • Risk factors:
    • Social isolation
    • Loneliness
    • Chronic physical conditions
    • Indoor comfort metrics

Exacerbate/cause mental disorders

Domain analysis

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OAs, mental health & IEQ

  • Temperature: Depression, dementia, MCI are significantly influenced by temperature.
    • Cold exposure effects: prolonged exposure to low indoor temperatures is associated with depressive symptoms, poor sleep, and reduced quality of life due to physiological stress responses
    • Temperature fluctuations: sudden changes in temperature (e.g., diurnal range) are linked to spikes in mental illness symptoms, particularly depression-related anxiety and hopelessness
    • Individuals with dementia have altered thermal sensitivity, requiring personalized temperature management to reduce agitation and improve sleep
    • Optimal Temperature Range: a thermoneutral zone of 20–24°C (68–75°F) is ideal for OAs; deviations from this range impair cognitive function, sleep quality, and emotional regulation.

Domain analysis

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OAs, mental health & IEQ

  • Air quality: exposure to pollutants like PM2.5, PM10, NO₂, and O₃ is consistently linked to increased risks of depression, anxiety, cognitive decline, and dementia.
    • These effects are driven by systemic and neuroinflammation, oxidative stress, and disrupted sleep and circadian rhythms
    • Indoor Pollutants: VOCs, CO₂, tobacco smoke, mold, and combustion emissions in residential and care settings contribute to inflammation, brain connectivity issues, and heightened anxiety and depression.
    • Pollution-related sleep disturbances and structural brain changes are intermediate mechanisms that worsen depressive symptoms, especially in older adults
    • Benefits of cleaner air: Improved indoor air quality through ventilation, filtration, and cleaner fuels has been shown to reduce depressive symptoms and enhance emotional well-being.

Domain analysis

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OAs, mental health & IEQ

  • Lighting: essential in regulating circadian rhythms, mood, cognitive functions in OAs.
    • Daytime light exposure: High-intensity light during the day (≥2,500 lux) enhances cognitive function and reduces depression by stabilizing circadian rhythms and improving sleep efficiency.
    • Indoor lighting satisfaction: Positive emotional well-being is linked to satisfaction with indoor lighting, while poor lighting increases loneliness, negative mood, and sleep issues.
    • Nighttime Light Risks: Exposure to indoor light above 5 lux at night disrupts circadian rhythms and melatonin production, increasing the risk of depression.
    • Appropriate lighting is a proven, non-drug strategy to support mental health, especially for OAs with mobility or cognitive impairments.

Domain analysis

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OAs, mental health & IEQ

  • Sleep and circadian rhythm: disruption of circadian rhythms (regulated primarily by light and temperature) plays a key role in linking environmental conditions to psychological outcomes.
    • Poor lighting, thermal discomfort, inadequate ventilation can trigger physiological stress, hormonal imbalances like melatonin suppression and elevated cortisol, and neuroinflammation, all of which are associated with mood disorders and sleep disturbances

Domain analysis

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A conceptual map

  • A map representing the main features of the domain at hand
  • Focuses on:
    • Identifying the main concepts…
    • … and their relationships
    • Identifying the main comfort metrics
  • Scope of OAIC: preventing the exacerbation of OAs’ mental issues by modifying indoor comfort when occupants are staying in a room

Conceptualization

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Clinical conceptualizations

  • Depression: Geriatric Depression Scale (GDS)

  • Anxiety: Geriatric Anxiety Inventory (GAI)

  • Sleep disorders: Geriatric Sleep Questionnaire (GSQ) - 6 items

Conceptualization

Scores ≥ 5 🡪 mild depression

5 < Scores ≤ 8 🡪 moderate depression

Scores > 8 🡪 severe depression

Scores ≥ 3 🡪 probable form of anxiety

Scores ≥ 15 🡪 presence of sleep disorders

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Reused ontoogies

  • SOSA (selected concepts, soft reuse)
    • sosa:Observation, sosa:Sensors, sosa:Actuator, sosa:Property
    • Other necessary object properties
  • Ontology of Units and Measure (import)

  • ICD
  • ICF

Necessary to represent essential concepts in the fields of smart objects and the measurements they perform within the indoor environment.

Fundamental to quantify and express the measurements performed within the indoor environment by sensors and to quantify the actuations provided by actuators.

To represent impairments, disabilities, and chronic conditions affecting an OA’s health condition.

Subsets – ICF Core Sets

Subsets – selected conditions from use cases

Conceptualization

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OAIC ontology

  • Developed with Protégé, OWL 2 DL
  • 102 classes
  • 30 object properties
  • 40 datatype properties
  • 90 individuals
  • 18 rules (SWRL)

Development

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OAIC ontology – ODP

  • Connecting an OA individual with its oaic:HealthCondition

ODP source: 10.1186/s13326-016-0049-1

Development

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OAIC – modelling comfort

  • Similar to a oaic:HealthCondition, each OA is linked to an OWL individual oaic:TailoredComfortSetting, which specifies for each comfort metrics the settings to avoid the exacerbations of his/her mental conditions

Development

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Rules

  • SWRL rules for:
    • Classifying an OA’s health condition
    • Checking whether a sosa:Observation individual value falls within the ranges specified by the oaic:TailoredComfortSetting if it is specified
    • Identifying the proper sosa:Actuator and activate it (by setting true the value of the oaic:activate datatype property) in case a value (i.e., a sosa:Observation) exceeds the threshold(s) represented in the oaic:ComfortSetting individual

Development

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Use case #1

Test

  • Mr. Arco
  • Retirement community (single room)
  • 82 years old
  • Mild depression (icd:6A71.0)
  • GDS = 7
  • COPD (icd:CA22)

Health condition requiring:

  • CO2 maximum level: 700 PPM
  • Ventilation

A sosa:Actuator (air purifier) is activated whenever a sosa:Observation has a CO2 maximum level ≥ than the CO2 maximum level modelled for mr. Arco’s oaic:ComfortSetting

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Use case #2

Test

  • Mrs. Rossi
  • Lives on her own
  • 76 years old
  • Chronic insomnia (icd:7A00)
  • Sleep function disorders (icd:VV01)

Physicians recommended:

  • ≈20° C. indoor temperature during sleep time
  • Blackout automatic shutters (<5 lux)

Two rules (leveraging the sosa:resultTime value attached to each sosa:Observation) enable:

  • Identify whenever the indoor temperature is 1.5 degrees lower or higher than the recommended temperature (modelled in Mrs. Rossi’s oaic:ComfortSetting) and activate the HVAC system
  • Assessing whether the illuminance level indoor meets the one modelled in Mrs. Rossi’s oaic:ComfortSetting and, if not, activating the blackout shutters to make complete dark within the room

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Limitations and future works

  • Current focus on single disorders 🡪 addressing multiple and complex conditions
  • Simplistic representation of actuation 🡪 this may change as OAIC is still in the early phases of the AgiSCOnt
  • Validation:
    • Stakeholders’ opinions
    • Systematic evaluation of the clinical inferences and their usefulness
  • OAIC currently considers only single occupants, not multi-occupant scenarios with differing health conditions

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Towards an ontology-based system to foster Older Adults’ Mental health via Indoor Comfort management

Daniele Spoladore: daniele.spoladore@cnr.it

JOWO 2025 – Promoting Healthy Aging through Semantic Enrichment of Solitude Research (PHASES)