wellness
Datasets
All datasets matching “wellness”wellness-tourism-customersshrec_wellness_dorm
Social Human Robot Embodied Conversation (SHREC) Dataset: Wellness Dorm Subset (RSS 2026)
The SHREC Wellness Dorm subset contains longitudinal, real-world human-robot interaction video data data from Jeong et al. (2020), where a robotic positive psychology coach was deployed in MIT student dormitories. Participants engaged in daily wellbeing sessions with the robot over the course of 1–4 weeks.
Authors: Dong Won Lee, Yubin Kim, Sooyeon Jeong, Denison Guvenoz, Parker… See the full description on the dataset page: https://huggingface.co/datasets/MIT-personal-robots/shrec_wellness_dorm.shrec_wellness_home
Social Human Robot Embodied Conversation (SHREC) Dataset - Wellness Home Subset (RSS 2026)
The SHREC Wellness Home subset contains real-world, longitudinal interaction video data from Jeong et al. (2023) recordings from an 8-week in-home study with adult participants aged 18–83. Participants engaged with a socially assistive robot designed to improve psychological well-being, affect, and readiness for change through evidence-based positive psychology interventions (PPIs).… See the full description on the dataset page: https://huggingface.co/datasets/MIT-personal-robots/shrec_wellness_home.tourism-wellness-datasettswap-wellness-benchmark
TSWAP — Thai Wellness Benchmark & Evaluation Release
Data and evaluation logs released with the paper "TSWAP: A Multilingual Retrieval-Augmented
Thai Wellness Advisor" (Pornthep Ukosaramig, Digital Touch Point Co., Ltd.; Kobkrit
Viriyayudhakorn, iApp Technology Co., Ltd.).
TSWAP is a deployed eight-language wellness advisor grounded, via RAG, in a verified knowledge
base of Thai traditional medicine (แพทย์แผนไทย / สมุนไพรไทย) and certified wellness providers —
live at… See the full description on the dataset page: https://huggingface.co/datasets/iapp/tswap-wellness-benchmark.LifeSnaps_dataset
PAPER: https://www.nature.com/articles/s41597-022-01764-x
BREQ-2. For the BREQ-2 scale, each item is again assigned to a factor on which that item is scored (i.e., of the
fve factors: (1) Amotivation, (2) External regulation, (3) Introjected regulation, (4) Identifed regulation, (5)
Intrinsic regulation). Once scores are assigned to all of the items, we calculate each user’s mean for every factor, according to the scoring instructions… See the full description on the dataset page: https://huggingface.co/datasets/wellness10/LifeSnaps_dataset.