• 'Smart saddle' could help equestrians hi

    From ScienceDaily@1:317/3 to All on Wed Jan 26 21:30:42 2022
    'Smart saddle' could help equestrians hit their stride

    Date:
    January 26, 2022
    Source:
    American Chemical Society
    Summary:
    Researchers have developed a prototype 'smart saddle' that
    could help equestrians improve their biomechanics. Moreover,
    the self-powered saddle can alert others when a rider takes a fall.



    FULL STORY ========================================================================== Skilled equestrians make advanced riding maneuvers, like jumps, spins
    and piaffes, look effortless. But good riding requires balance and subtle
    cues to the horse, many of which are given through the rider's posture,
    seat and legs.

    Now, researchers reporting in ACS Nano developed a prototype "smart
    saddle" that could help equestrians improve their biomechanics. Moreover,
    the self- powered saddle can alert others when a rider takes a fall.


    ==========================================================================
    Big data collection and analysis are becoming important components of
    many competitive sports because they provide real-time information on
    athletes' performance and fitness. However, most systems are powered
    by batteries, often making them bulky and inflexible. In contrast,
    small, lightweight triboelectric nanogenerators (TENGs), which convert mechanical energy into electricity, are being tested for a variety of applications, from harvesting the energy of ocean waves to charging
    cell phones through walking. In addition to powering themselves, TENGs
    can convert mechanical stimuli, such as pressure, touch or motion,
    into electrical signals. Ding Nan, Baodong Chen, Zhong Lin Wang and
    colleagues wanted to adapt TENGs to a smart saddle for challenging and potentially dangerous equestrian sports.

    The researchers made a thin, flexible, disk-shaped TENG that flattens when depressed and then rebounds when the pressure is removed. Under pressure,
    the internal layers of the TENG compress, transferring electrons from
    one electrode to another and generating a current, which stops when the pressure is released.

    The team placed an array of seven TENGs on the top surface of a saddle
    so they could detect differences in pressure in various regions of the
    seat. Electrical signals from the array revealed whether a rider was
    leaning forward, sitting in an upright position or leaning backward. The
    smart saddle also detected when a person was standing up and sitting
    down (a motion called "posting" in the equestrian world). When a rider
    falls off, the system can transmit a wireless signal to alert others,
    a safety feature that could allow an injured rider to be quickly found
    and treated, which is especially important when riding alone.

    The self-powered smart saddle, which has a response time of 16
    milliseconds, could someday provide real-time statistical data and fall detection to equestrians and their coaches, the researchers say.

    The authors acknowledge funding from the Natural Science Foundation of
    Beijing Municipality, the National Natural Science Foundation of China,
    the National Key R&D Project from Ministry of Science and Technology, the Beijing Municipal Science and Technology Commission, the Inner Mongolia scientific and technological achievements transformation project and
    the Inner Mongolia autonomous region major science and technology program.

    ========================================================================== Story Source: Materials provided by American_Chemical_Society. Note:
    Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Yutao Hao, Jing Wen, Xiaobo Gao, Ding Nan, Juan Pan, Yuhan Yang,
    Baodong
    Chen, Zhong Lin Wang. Self-Rebound Cambered Triboelectric
    Nanogenerator Array for Self-Powered Sensing in Kinematic
    Analytics. ACS Nano, 2022; 16 (1): 1271 DOI: 10.1021/acsnano.1c09096 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/01/220126090529.htm

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