El sector del golf

Motion sensors technology makes it possible to accurately identify, track and analyse movement. The data that can be acquired using such devices support the diagnosis and the rehabilitation process [24] by allowing therapists to precisely assess the im- pact of clinical interventions on the patients’ everyday life and recovery [25]. Among the many different sensors that can be used for monitoring patients during rehabilita- tion, MEMS (Micro-Electro-Mechanical Systems) inertial sensors have been shown to have great potentials. The progress of miniaturization and their decreasing cost allow to incorporate them in compact, non-obtrusive continuous monitoring devices easily attachable to the body [26], empowering the development of Wireless Body Area Networks (WBANs) [27,28]. In particular, accelerometers can provide reliable

information as well as objective and quantitative measurements when placed on di- fferent parts of the body [29]. For this reason, several studies about their use for body motion capture have been published recently.

In [30] it is stated that the use of accelerometers offers a practical and low-cost method for monitoring human movements, while providing objective and reliable measurements, including assessment of physical activity level and classification of the movements performed by subjects. In their review of the state of the art, the authors have found out that tri-axial accelerometers are able to provide valid and sta- ble measurements of physical activity levels when compared to other indicators of functional capacity. For this reason, accelerometers have been used to study physi- cal activity in many different experiments. One important application of this kind of sensors is within the tests of postural sway, which usually need to be set up and con- ducted by an external observer, different from the patient, where these sensors have shown to be a reliable tool for measuring balance while standing and walking. Even more, the studies that have been undertaken demonstrated their utility for monitoring human movements and quantitatively measuring important parameters of movement in an unsupervised home environment. This implies some technical requirements, as their usability, power supply and trustworthy wireless communications, for example. [31] confirms that accelerometers have been widely accepted as useful and practi- cal sensors for wearable devices to measure and assess physical activity. It concludes that sensor-based measurement of human activities can provide quantitative assess- ment of physical activity. The main advantage is that using these techniques enables automatic, continuous and long-term activity measurement of subjects in a free-living environment.

[32] makes use of a tri-axial accelerometer for posture sensing to be used in activity recognition. Experiments were done for eight different activities –standing, walking, running, climbing up stairs, climbing down stairs, sit-ups, vacuuming and brushing teeth– showing that these can be recognized with fairly high accuracy. Any- way, as expected, some of the activities, like brushing teeth, were comparatively harder to recognize than others due to the fact that there was just one accelerome- ter and that it was worn near the waist. In [33] an accelerometer attached to a belt,

centered in the back of the person, is used for body posture recognition, while in [34] vital body signals as posture, respiration rate, and body activities like walking and running, are monitored by placing one of them in a t-shirt.

Due to the potential use of accelerometers in a clinical setting and considering their reliability and low cost, the research performed in [35] is related to gait analy- sis and balance evaluation for elderly people. Being able to assess the risk of falls thanks to the quantitative measures of the gait provided by the accelerometers, the 24-hour ambulatory activity levels can be objectively quantified. Human gait mode- lling for helping in the diagnosis of walking and movement disorders or rehabilitation programs is also approached in [36] and [37]. The work presented in [38] goes in a similar direction. It consists on a wearable platform intended for long-term ambula- tory health monitoring with real-time data streaming and context classification. For fall detection and the classification of other body movements, [39] and [40] use a small module which contains a high resolution accelerometer. They demonstrate its advantages for acquiring motion information due to its precision and size, as it is not intrusive for the subject.

As said in [41], a significant application area is remote monitoring, more specifi- cally home-based rehabilitation monitoring systems, already introduced by [5], both for elderly people who live alone and are in need of additional support, and for people with physical disabilities. It could allow to check whether the patient is able to per- form her/his physical therapy exercises in the correct and most efficient manner, and provide feedback to enable proper performance of the exercises. A portable patient- monitoring system might facilitate patient rehabilitation out of the hospital environ- ment, enabling faster recovery and decreasing number of injuries. Even more, having a system that allows to bring the rehabilitation into their own house, might help the patients to perform exercises much more comfortably in a known environment, pre- venting them from getting stressed while being monitored in a rehabilitation centre or similar.

In this direction, [42] proposes a portable physical rehabilitation monitoring sys- tem for hip-and-knee-replacement rehabilitation, which makes use of accelerometers for sensing the patient’s movements. It allows one to visualize selected data in real

time on a PDA screen and to archive relevant data for later analysis by a specialist. [43] proposes a prototypical WBAN implementation for computer-assisted physical rehabilitation applications and ambulatory monitoring which provides guidance and feedback to the user, by generating warnings based on the user’s state, level of ac- tivity, and environmental conditions in real time. On the other hand, the purpose of the study in [44] is to develop a motion tracking device that can be integrated within a home-based rehabilitation system for stroke patients. In particular, it integrates the measurements from the accelerometers and gyroscopes for acquiring the data related to the upper limb movements in real time. This work has afterwards been extended in [2], which presents an upper limb motion tracking system with two sensors near the wrist and elbow joints which shows promising results in view of its integration in a rehabilitation platform for describing the upper limb movements of a patient.