According to a United Nations’ report on World Population Aging (2020), the number of people in the world aged 60 or over is projected to grow to 1.5 billion by the year 2050. Aging can come with various complexities and challenges, such as decline in the physical, cognitive and mental health of a person. These changes affect a person’s everyday life, resulting in decreased social participation, lack of physical activity, and vulnerability to injury and disability that can be exacerbated by the occurrence of various acute health events, such as strokes, or long term illnesses.

The field of assistive technology amalgamates several multi-disciplinary areas including data mining, rehabilitation engineering, and clinical studies. The idea of assistive technology solutions is to promote independent, active and healthy aging with a specific focus on older adults, and those living with mild cognitive impairments.

The COVID-19 pandemic has highlighted the challenges encountered by vulnerable populations in terms of not getting adequate care, difficulties in access to healthcare services and lack of necessary support to stay independent and safe. Many clinical treatments and rehabilitation services have gone virtual due to strict social distancing guidelines that have added more complexity to supporting the older population.

Collecting and mining health data using assistive technology devices is a challenging task. Leveraging Artificial Intelligence (AI) techniques is essential to make advancements in the field of aging and rehabilitation. Building AI models on vast amounts of health data from older adults will facilitate independent assisted living, promote healthy living, and manage rehabilitation routines effectively.

** Call for Papers **

ARIAL@ICDM22 will be held in Orlando, FL, USA. In this workshop, we invite previously unpublished and novel submissions in the following areas (pertaining to aging and rehabilitation), but not limited to:

* Methods, protocols and challenges for multimodal data collection, data annotation, and data labeling with older adult populations.
* Development and deployment of long-term sensor-based monitoring systems.
* Methodologies for big data, large-scale data mining, including cloud and edge computing.
* Data cleaning, curation, sharing and harmonization.
* Data analytics and visualization techniques for healthcare data of older adults.
* Data mining challenges such as handling missing data, dealing with mixed, imbalanced, poorly labeled and noisy data.
* Techniques for tele-rehabilitation/virtual rehabilitation, telemedicine and remote monitoring.
* Audio/video, multimodal interaction for patient engagement, exercise monitoring and successful delivery of rehabilitation.
* Addressing privacy concerns of patient data, e.g., privacy-protecting sensing modalities, federated learning and differential privacy.
* Machine learning and Deep Learning algorithms to identify harmful, life-threatening, abnormal behaviors in older care settings.
* AI approaches for continuous streaming, monitoring and analysis of health, activity, contextual, and online data for older adults.
* Techniques for handling data biases, and other biases related to sex, gender, ethnicity and age (e.g., fair machine learning strategies).
* Data mining methods for measuring health indicators, progression of physical and cognitive health, e.g., frailty, dementia, social isolation, mobility, mental health, gait stability.
* AI approaches for data fusion from multi-modal sensor interaction and ensemble algorithm development (e.g., multi-view learning approaches).

** Important Dates **
Paper submissions: September 17, 2022 (anywhere in the world)
Paper notifications: October 08 , 2022
Camera-ready deadline for the final version of accepted papers: To be announced later
Paper Registration Date: To be announced later
Workshop date: November 28, 2022

** Submission Guidelines **
Please use this link (https://wi-lab.com/cyberchair/2022/icdm22/scripts/submit.php?subarea=S06&undisplay_detail=1) to submit your papers. All papers must be original and not simultaneously submitted to another journal or conference. We request you to submit Full papers - 5 pages (including references). The review process will be double blind; therefore, authors must not write their names, contact details or affiliations in their papers at the time of submission. The accepted papers will be published in IEEE Xplore with a DOI.

Please use the IEEE 2-column format for paper submission (https://www.ieee.org/conferences/publishing/templates.html).

Note: BioMedical Engineering OnLine (I.F. 3.9, part of Springer Nature) has agreed to publish extended papers presented at ARIAL workshop at a discounted price. The pricing details will be announced later.

**Committees**
*Workshop Co-chairs*
Shehroz Khan, KITE, University Health Network, Canada.
Dinesh Jayagopi, IIIT, Bangalore, India.
Luca Romeo, University of Macerata, Italy.
Amir Ahmad, United Arab Emirate University, UAE.

*Organizing Committee*
Ali Abedi, KITE, University Health Network, Canada.
Elham Khodabandehloo, KITE, University Health Network, Canada.

*Program Committee*
Abhinav Dhall, Indian Institute of Technology Ropar, India
Daniele Riboni, University of Cagliari , Italy
Jamal Deen, McMaster University, Canada
Harshit Kumar, IBM Research, IndiaJosé Zariffa, University of Toronto, Canada
Ladislau Bölöni, University of Central Florida, USA
Mah Parsa, Centre de Recherche Informatique de Montréal, Canada
Michele Bernardini, Marche Polytechnic University, Italy
Narges Armanfard, McGill University, Canada
Riccardo Rosati, Marche Polytechnic University, Italy
Ryan Koh, Toronto Rehabilitation Institute, Canada
Veselka Boeva, Blekinge Institute of Technology, Sweden

*Venue*
ARIAL@ICDM2022 will be held in person at Hilton Orlando, 6001 Destination Pkwy, Orlando, Florida 32819, USA.

*Contact*
All questions about submissions should be emailed to shehroz.khan@uhn.ca / ali.abedi@uhn.ca