Design and Validity of a Smart Healthcare and Control System for Electric Bikes.
Eli Gabriel Aviña BravoFelipe Augusto Sodre Ferreira de SousaChristophe EscribaPascal AccoFranck GiraudJean-Yves FourniolsGeorges Soto-RomeroPublished in: Sensors (Basel, Switzerland) (2023)
This paper presents the development of an electronic system that converts an electrically assisted bicycle into an intelligent health monitoring system, allowing people who are not athletic or who have a history of health issues to progressively start the physical activity by following a medical protocol (e.g., max heart rate and power output, training time). The developed system aims to monitor the health state of the rider, analyze data in real-time, and provide electric assistance, thus diminishing muscular exertion. Furthermore, such a system can recover the same physiological data used in medical centers and program it into the e-bike to track the patient's health. System validation is conducted by replicating a standard medical protocol used in physiotherapy centers and hospitals, typically conducted in indoor conditions. However, the presented work differentiates itself by implementing this protocol in outdoor environments, which is impossible with the equipment used in medical centers. The experimental results show that the developed electronic prototypes and the algorithm effectively monitored the subject's physiological condition. Moreover, when necessary, the system can change the training load and help the subject remain in their prescribed cardiac zone. This system allows whoever needs to follow a rehabilitation program to do so not only in their physician's office, but whenever they want, including while commuting.
Keyphrases
- healthcare
- heart rate
- randomized controlled trial
- public health
- quality improvement
- physical activity
- mental health
- blood pressure
- air pollution
- health information
- heart rate variability
- particulate matter
- emergency department
- left ventricular
- electronic health record
- primary care
- big data
- human health
- body mass index
- machine learning
- heart failure
- climate change
- body composition