A mobile APP-based, customizable automated device for self-administered olfactory testing and an implementation of smell identification test

Zhihao Lan, Qing X. Yang, Zhi Hong Lyu, Cailing Feng, Liansheng Wang, Baowei Ji, Xuefei Yu, Sherman Xuegang Xin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Olfactory tests are used for the evaluation of ability to detect and identify common odors in humans psychophysically. Olfactory tests are currently administered by professionals with a set of given odorants. Manual administration of such tests can be labor and cost intensive and data collected as such are confounded with experimental variables, which adds personnel costs and introduces potential errors and data variability. For large-scale and longitudinal studies, manually recorded data must be collected and compiled from multiple sites. It is difficult to standardize the way data are collected and recorded. There is a need for a computerized smell test system for psychophysical and clinical applications. A mobile digital olfactory testing system (DOTS) was developed, consisting of an odor delivery system (DOTS-ODD) and a mobile application program (DOTS-APP) connected wirelessly. The University of Pennsylvania Smell Identification Test was implemented in DOTS and compared to its commercial product on a cohort of 80 normosmic subjects and a clinical cohort of 12 Parkinson’s disease patients. A test–retest was conducted on 29 subjects of the normal cohort. The smell identification scores obtained from the DOTS and standard UPSIT commercial test are highly correlated (r = 0.714, P < 0.001), and test–retest reliability coefficient was 0.807 (r = 0.807, P < 0.001). The DOTS is customizable and mobile compatible, which allows for the implementation of standardized olfactory tests and the customization of investigators’ experimental paradigms. The DOTS-APP on mobile devices offers capabilities for a broad range of on-site, online, or remote clinical and scientific chemosensory applications.

Original languageEnglish (US)
Article numberbjad022
JournalChemical senses
Volume48
DOIs
StatePublished - 2023

All Science Journal Classification (ASJC) codes

  • Physiology
  • Sensory Systems
  • Physiology (medical)
  • Behavioral Neuroscience

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