! " ! # ! $ ! %%&’() ! # ! * + ! ! ! ! I. INTRODUCTION Body posture monitoring is an emerging area of study and development, with applications in areas such as sports, healthcare and entertainment. Posture monitoring systems based on wireless body area networks (WBANs) [1] present several advantages compared to conventional systems based on cameras, because, unlike the latter, the former can be used in uncontrolled environments, under any lighting conditions and without line of sight to the receptor. WBANs require small,sized wireless sensors that can be conveniently placed in the user’s body, as well as low power consumption hardware and energy efficient protocols, in order to provide adequate battery lifetime [2]. In a WBAN usually sensors sent the collected data to a central station (e.g., a personal computer) with capacity to process and store the data. With the technological advancement, smaller personal devices, such as smartphones, also started to become suitable for these tasks, with the advantage of greater portability. The posture of an athlete during the cycling activity can dramatically influence his performance. Several studies in this area were made, either with elite athletes or amateur cyclists. The aero position, where the cyclist adopts a lowered position with the trunk almost horizontal and the This work has been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the project: PEst,OE/EEA/UI04436/2015. António F. Maio is with Centro Algoritmi, University of Minho, Campus of Azurém, Guimarães, 4800,058, Portugal (e,mail: a60142@alunos.uminho.pt). José A. Afonso is with MEMS,UMinho, University of Minho, Campus of Azurém, Guimarães, 4800,058, Portugal (phone: 351,253510190; fax: 351,253510189; e,mail: jose.afonso@dei.uminho.pt). arms extended forward with elbows tucked in, has the advantage of reducing the drag imposed by wind resistance. However, in [3], the authors conclude that the upright position allows higher VO 2 , ventilation, heart rate, and workload for untrained cyclists performing with maximal effort. Moreover, the upright position makes the cycling exercise less costly during steady state. In [4], the authors conclude that the posture has a very large effect on the performance of active cyclists during constant,load exercises. Besides the trunk posture, the performance of cyclists can be affected if the angle of the knee is not the most correct. In [5], anaerobic tests were performed with trained and untrained cyclists. Results show that the seat should be adjusted to allow the leg to be flexed by 25,35 degrees for untrained cyclists, in order to contribute to the prevention of injuries and increase the performance. Mobile sensing is an attractive emerging area of research and development [6], [7] that uses sensor data collected by users’ smartphones to extract relevant information. Some of these research works are applied to cycling, monitoring sensor data from the bicycle, the user’s body or the environment [8], [9], [10]. BikeNet [8] is a project that performs the mapping of user experience based on various sensors adapted to a conventional bicycle using a network of wireless sensors based on the IEEE 802.15.4 standard. In order to provide the interface between the sensor network and a smartphone, this system uses an IEEE 802.15.4/Bluetooth gateway. Data collection focuses on parameters such as noise and carbon dioxide levels, speed, geographical location and user’s stress level. The cyclist’s posture is not monitored. The Copenhagen Wheel project [9] developed a wheel that can be adapted in a conventional bicycle in order to turn it into an electric bike. An iPhone smartphone communicates with the central part of the wheel (hub) using Bluetooth, providing geographical location services and allowing the user to manually lock/unlock the bike, change the gear and adjust the level of actuation of the electric motor. This system does not collect any physiological data from the cyclist. This paper presents a system that allows the real,time monitoring of the posture of cyclists through the use of sensor modules placed on the body of the athlete, which send the collected data to an Android smartphone. These modules were developed by us and integrate 3,axis accelerometers, magnetometers and gyroscopes. The wireless communication between the sensor modules and the smartphone is based on Bluetooth Low Energy (BLE) [11], which is a wireless technology optimized for ultra,low power consumption, designed to be used on Wireless Cycling Posture Monitoring Based on Smartphones and Bluetooth Low Energy António F. Maio and José A. Afonso, Proceedings of the World Congress on Engineering 2015 Vol I WCE 2015, July 1 - 3, 2015, London, U.K. ISBN: 978-988-19253-4-3 ISSN: 2078-0958 (Print); ISSN: 2078-0966 (Online) WCE 2015