An innovative running wheel-based mechanism for improved rat training performance

Chi Chun Chen, Chin Lung Yang, Ching Ping Chang

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


This study presents an animal mobility system, equipped with a positioning running wheel (PRW), as a way to quantify the efficacy of an exercise activity for reducing the severity of the effects of the stroke in rats. This system provides more effective animal exercise training than commercially available systems such as treadmills and motorized running wheels (MRWs). In contrast to an MRW that can only achieve speeds below 20 m/min, rats are permitted to run at a stable speed of 30 m/min on a more spacious and high-density rubber running track supported by a 15 cm wide acrylic wheel with a diameter of 55 cm in this work. Using a predefined adaptive acceleration curve, the system not only reduces the operator error but also trains the rats to run persistently until a specified intensity is reached. As a way to evaluate the exercise effectiveness, real-time position of a rat is detected by four pairs of infrared sensors deployed on the running wheel. Once an adaptive acceleration curve is initiated using a microcontroller, the data obtained by the infrared sensors are automatically recorded and analyzed in a computer. For comparison purposes, 3 week training is conducted on rats using a treadmill, an MRW and a PRW. After surgically inducing middle cerebral artery occlusion (MCAo), modified neurological severity scores (mNSS) and an inclined plane test were conducted to assess the neurological damages to the rats. PRW is experimentally validated as the most effective among such animal mobility systems. Furthermore, an exercise effectiveness measure, based on rat position analysis, showed that there is a high negative correlation between the effective exercise and the infarct volume, and can be employed to quantify a rat training in any type of brain damage reduction experiments.

Original languageEnglish
Article numbere54354
JournalJournal of Visualized Experiments
Issue number115
Publication statusPublished - 2016 Sept 19

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)


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