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    • 1. 发明申请
    • RECOGNIZING GESTURES FROM FOREARM EMG SIGNALS
    • 从FOREARM EMG信号识别GESTURES
    • US20090327171A1
    • 2009-12-31
    • US12146471
    • 2008-06-26
    • Desney TanDan MorrisScott SaponasRavin Balakrishnan
    • Desney TanDan MorrisScott SaponasRavin Balakrishnan
    • G06F15/18
    • G06N99/005G06F3/015G06F3/017
    • A machine learning model is trained by instructing a user to perform proscribed gestures, sampling signals from EMG sensors arranged arbitrarily on the user's forearm with respect to locations of muscles in the forearm, extracting feature samples from the sampled signals, labeling the feature samples according to the corresponding gestures instructed to be performed, and training the machine learning model with the labeled feature samples. Subsequently, gestures may be recognized using the trained machine learning model by sampling signals from the EMG sensors, extracting from the signals unlabeled feature samples of a same type as those extracted during the training, passing the unlabeled feature samples to the machine learning model, and outputting from the machine learning model indicia of a gesture classified by the machine learning model.
    • 通过指示用户执行禁止的手势,从前臂中的肌肉位置任意布置的EMG传感器的采样信号,从采样信号中提取特征样本,按照根据 指示执行相应的手势,并用标记的特征样本训练机器学习模型。 随后,可以使用经过训练的机器学习模型,通过对来自EMG传感器的信号进行采样,从信号提取与训练期间提取的相似类型的未标记的特征样本,将未标记的特征样本传递到机器学习模型, 从机器学习模型标记输出由机器学习模型分类的手势。
    • 2. 发明授权
    • Recognizing gestures from forearm EMG signals
    • 识别前臂EMG信号的手势
    • US08447704B2
    • 2013-05-21
    • US12146471
    • 2008-06-26
    • Desney TanDan MorrisScott SaponasRavin Balakrishnan
    • Desney TanDan MorrisScott SaponasRavin Balakrishnan
    • G06F15/18
    • G06N99/005G06F3/015G06F3/017
    • A machine learning model is trained by instructing a user to perform proscribed gestures, sampling signals from EMG sensors arranged arbitrarily on the user's forearm with respect to locations of muscles in the forearm, extracting feature samples from the sampled signals, labeling the feature samples according to the corresponding gestures instructed to be performed, and training the machine learning model with the labeled feature samples. Subsequently, gestures may be recognized using the trained machine learning model by sampling signals from the EMG sensors, extracting from the signals unlabeled feature samples of a same type as those extracted during the training, passing the unlabeled feature samples to the machine learning model, and outputting from the machine learning model indicia of a gesture classified by the machine learning model.
    • 通过指示用户执行禁止的手势,从前臂中的肌肉位置任意布置的EMG传感器的采样信号,从采样信号中提取特征样本,按照根据 指示执行相应的手势,并用标记的特征样本训练机器学习模型。 随后,可以使用经过训练的机器学习模型,通过对来自EMG传感器的信号进行采样,从信号提取与训练期间提取的相似类型的未标记的特征样本,将未标记的特征样本传递到机器学习模型, 从机器学习模型标记输出由机器学习模型分类的手势。
    • 3. 发明授权
    • Magnetic inductive charging with low far fields
    • 低磁场感应充电
    • US08686684B2
    • 2014-04-01
    • US12413217
    • 2009-03-27
    • Jim TurnerScott SaponasDesney TanDan Morris
    • Jim TurnerScott SaponasDesney TanDan Morris
    • H02J7/00
    • H02J50/12H02J7/025H02J50/40
    • A charging station wirelessly transmits power to mobile electronic devices (MEDs) each having a planar-shaped receiver coil (RC) and a capacitor connected in parallel across the RC. The station includes a planar charging surface, a number of series-interconnected bank A source coils (SCs), a number of series-interconnected bank B SCs, and electronics for energizing the SCs. Each SC generates a flux field perpendicular to the charging surface. The bank A and bank B SCs are interleaved and alternately energized in a repeating duty cycle. The coils in each bank are also alternately wound in a different direction so that the fields cancel each other out in a far-field environment. Whenever an MED is placed in close proximity to the charging surface, the fields wirelessly induce power in the RC. The MEDs can have any two-dimensional orientation with respect to the charging surface.
    • 充电站向具有平面状接收线圈(RC)的移动电子设备(MED)和跨RC并联连接的电容器无线地发送电力。 该站包括平面充电表面,多个串联互连的库A源线圈(SC),多个串联互连的库B SC和用于激励SC的电子器件。 每个SC产生垂直于充电表面的磁通场。 存储体A和存储体B SC交替地并以重复占空比交替地通电。 每个组中的线圈也以不同的方向交替地缠绕,使得场在远场环境中相互抵消。 无论何时MED被放置在靠近充电表面的地方,场都无线地在RC中引起电力。 MED可以相对于充电表面具有任何二维取向。
    • 4. 发明申请
    • MAGNETIC INDUCTIVE CHARGING WITH LOW FAR FIELDS
    • 低电场磁感应充电
    • US20100244767A1
    • 2010-09-30
    • US12413217
    • 2009-03-27
    • Jim TurnerScott SaponasDesney TanDan Morris
    • Jim TurnerScott SaponasDesney TanDan Morris
    • H02J7/00
    • H02J50/12H02J7/025H02J50/40
    • A charging station wirelessly transmits power to mobile electronic devices (MEDs) each having a planar-shaped receiver coil (RC) and a capacitor connected in parallel across the RC. The station includes a planar charging surface, a number of series-interconnected bank A source coils (SCs), a number of series-interconnected bank B SCs, and electronics for energizing the SCs. Each SC generates a flux field perpendicular to the charging surface. The bank A and bank B SCs are interleaved and alternately energized in a repeating duty cycle. The coils in each bank are also alternately wound in a different direction so that the fields cancel each other out in a far-field environment. Whenever an MED is placed in close proximity to the charging surface, the fields wirelessly induce power in the RC. The MEDs can have any two-dimensional orientation with respect to the charging surface.
    • 充电站向具有平面状接收线圈(RC)的移动电子设备(MED)和跨RC并联连接的电容器无线地发送电力。 该站包括平面充电表面,多个串联互连的库A源线圈(SC),多个串联互连的库B SC和用于激励SC的电子器件。 每个SC产生垂直于充电表面的磁通场。 存储体A和存储体B SC交替地并以重复占空比交替地通电。 每个组中的线圈也以不同的方向交替地缠绕,使得场在远场环境中相互抵消。 无论何时MED被放置在靠近充电表面的地方,场都无线地在RC中引起电力。 MED可以相对于充电表面具有任何二维取向。