WO2021143156A1 - 一种基于智能手表的2d移动轨迹识别方法和系统 - Google Patents

一种基于智能手表的2d移动轨迹识别方法和系统 Download PDF

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WO2021143156A1
WO2021143156A1 PCT/CN2020/113805 CN2020113805W WO2021143156A1 WO 2021143156 A1 WO2021143156 A1 WO 2021143156A1 CN 2020113805 W CN2020113805 W CN 2020113805W WO 2021143156 A1 WO2021143156 A1 WO 2021143156A1
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signal data
smart watch
gyroscope
threshold
data
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PCT/CN2020/113805
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English (en)
French (fr)
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伍楷舜
陈林
李聪
黄彦道
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深圳大学
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Priority to US17/792,698 priority Critical patent/US20230076452A1/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/02—Details
    • H04L12/12—Arrangements for remote connection or disconnection of substations or of equipment thereof
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/2803—Home automation networks
    • H04L12/2816—Controlling appliance services of a home automation network by calling their functionalities
    • H04L12/282—Controlling appliance services of a home automation network by calling their functionalities based on user interaction within the home
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C19/00—Gyroscopes; Turn-sensitive devices using vibrating masses; Turn-sensitive devices without moving masses; Measuring angular rate using gyroscopic effects
    • G01C19/56—Turn-sensitive devices using vibrating masses, e.g. vibratory angular rate sensors based on Coriolis forces
    • G01C19/5776—Signal processing not specific to any of the devices covered by groups G01C19/5607 - G01C19/5719
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/183—Compensation of inertial measurements, e.g. for temperature effects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/16—Constructional details or arrangements
    • G06F1/1613—Constructional details or arrangements for portable computers
    • G06F1/163—Wearable computers, e.g. on a belt
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/014—Hand-worn input/output arrangements, e.g. data gloves
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017—Gesture based interaction, e.g. based on a set of recognized hand gestures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03—Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/033—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor
    • G06F3/0346—Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M1/00—Substation equipment, e.g. for use by subscribers
    • H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
    • H04M1/724—User interfaces specially adapted for cordless or mobile telephones
    • H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
    • G—PHYSICS
    • G04—HOROLOGY
    • G04C—ELECTROMECHANICAL CLOCKS OR WATCHES
    • G04C3/00—Electromechanical clocks or watches independent of other time-pieces and in which the movement is maintained by electric means
    • G04C3/001—Electromechanical switches for setting or display
    • G04C3/002—Position, e.g. inclination dependent switches
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/2803—Home automation networks
    • H04L2012/284—Home automation networks characterised by the type of medium used
    • H04L2012/2841—Wireless
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M2250/00—Details of telephonic subscriber devices
    • H04M2250/12—Details of telephonic subscriber devices including a sensor for measuring a physical value, e.g. temperature or motion

Definitions

  • the present invention relates to the technical field of smart device interaction, in particular to a method and system for 2D movement track recognition based on smart watches.
  • the purpose of the present invention is to overcome the above-mentioned shortcomings of the prior art and provide a smart watch-based 2D movement track recognition method and system, which can realize the gesture track tracking of the smart watch wearer.
  • a 2D movement track recognition method based on a smart watch includes the following steps:
  • using the acceleration signal data to estimate the tilt angle of the smart watch and using the tilt angle to correct the gyroscope signal data includes the following sub-steps:
  • using the corrected gyroscope signal data to calculate the angle value information of the smart watch and estimate the coordinate points includes the following sub-steps:
  • the method of the present invention further includes: after obtaining the estimated coordinate points, broadcasting the coordinate points to the maintained client list.
  • the acquired accelerometer signal data and gyroscope signal data of the smart watch are processed using Butterworth filtering.
  • a 2D movement track recognition system based on a smart watch includes: a module for acquiring accelerometer signal data and gyroscope signal data of a smart watch; used to estimate the tilt angle of the smart watch using the acceleration signal data and correct the gyroscope signal data using the tilt angle The module; used to use the corrected gyroscope signal data to calculate the angle value information of the smart watch and estimate the coordinate point of the module.
  • the present invention has the advantage of being able to expand the functions of the smart watch without changing the software/hardware of the smart watch, and realize the track tracking and recording of continuous gestures.
  • the use of trajectory tracking gestures to continuously move and smoothly control the target device is realized, which enriches the application scenarios of smart watches.
  • Fig. 1 is a flowchart of a 2D movement track recognition method based on a smart watch according to an embodiment of the present invention
  • Figure 2 is a flow chart of gyroscope coordinate correction according to an embodiment of the present invention.
  • Fig. 3 is a schematic diagram of Euler angles according to an embodiment of the present invention.
  • the 2D movement track recognition method based on the smart watch includes the following steps:
  • Step S1 Collect the accelerometer and gyroscope sensor signals of the smart watch.
  • the accelerometer and gyroscope built into the smart watch are used for signal collection, and the acceleration signal data and gyroscope signal data of the smart watch are obtained. Further, in order to eliminate noise or abnormal data, the collected signal can be filtered, for example, Butterworth filtering is used to process the collected data.
  • the accelerometer can sense acceleration in any direction, and characterize the magnitude and direction of the axial acceleration by measuring the force of the smart watch in a certain axis.
  • the gyroscope measures the angle between the vertical axis of the gyro rotor in the three-dimensional coordinate system and the smart watch, and calculates the angular velocity. The angle and angular velocity are used to determine the motion state of the object in the three-dimensional space. Taking three-axis accelerometer and three-axis gyroscope as examples, the signal data of the x, y, and z axes of the accelerometer and gyroscope can be obtained. Since the smart watch is closely attached to the user's hand, these data can reflect the user's gesture Sports situation.
  • Step S2 use the accelerometer signal data to estimate the tilt angle and correct the gyroscope signal data.
  • the accelerometer signal data is used to estimate the tilt angle of the smart watch, and the gyroscope signal data is corrected.
  • correcting gyroscope data using accelerometer data includes the following steps:
  • the initial tilt angle ⁇ is 0, at this time cos ⁇ and sin ⁇ are 1, 0 respectively;
  • Collect and use Butterworth filtered accelerometer X, Y, Z axis data denoted as a x , a y , a z
  • collect and use Butterworth filtered gyroscope X, Y, Z axis data denote Is g x , g y , g z
  • the sampling frequency of the sensor of the smart watch device is denoted as f (unit Hz);
  • the energy threshold and the counting threshold of the embodiment of the present invention can be set to appropriate values according to application scenarios and the like, which is not limited in the present invention.
  • Step S3 using the corrected gyroscope signal data to calculate the angle value of the smart watch in the current state.
  • Step S4 sending the result to the connected client.
  • the specific steps include: after the system is started, it starts to monitor the request to connect to the system using Bluetooth, Wi-Fi and other protocols, and maintains a list of connected clients; when the 2D movement track recognition system detects the gesture signal, it broadcasts the coordinate points Give the list of maintained clients.
  • the present invention also provides a 2D movement track recognition system based on a smart watch, which is used to implement one or more aspects of the above method.
  • the system includes: a signal acquisition module, which is used to collect the signal data of the accelerometer and gyroscope sensor on the smart watch and uses Butterworth filtering to process the collected data; a signal correction module, which is used to use the accelerometer signal data Estimate the tilt angle of the smart watch and correct the gyroscope signal data; the calculation and detection module is used to calculate the angle value (pitch angle, yaw angle, yaw angle, etc.) of the smart watch in the current state using the corrected gyroscope signal data. Roll angle) and estimate the current coordinate point (x, y); data transmission module, which is used to send the coordinate point to the client connected to the system using Bluetooth, Wi-Fi and other protocols.
  • a signal acquisition module which is used to collect the signal data of the accelerometer and gyroscope sensor on the smart watch and uses Butterworth filtering to process the collected data
  • a signal correction module which is used to use the accelerometer signal data Estimate the tilt angle of the smart watch and correct the gyr
  • the signal correction module further includes:
  • Data collection and recording unit used to collect and use Butterworth filtered accelerometer X, Y, Z axis data as a x , a y , a z , collect and use Butterworth filtered gyroscope X, Y , Z axis data is denoted as g x , g y , g z ;
  • the sensor sampling frequency of the smart watch device is denoted as f;
  • the initial tilt angle ⁇ is 0, at this time cos ⁇ and sin ⁇ are 1, 0 respectively;
  • Correction angular velocity unit used to correct the y-axis and z-axis angular velocity signal data of the gyroscope by using the tilt angle ⁇ information: in, Is the corrected y-axis data of the gyroscope, It is the corrected z-axis data of the gyroscope.
  • calculation and detection module further includes:
  • Coordinate point calculation unit used to set the basis vector in the two-dimensional vertical coordinate system as a unit vector Then the current coordinate point is
  • the data transmission module further includes:
  • Monitoring protocol unit After the system is started, it is used to start monitoring the request to connect to the system using Bluetooth, Wi-Fi and other protocols, and maintain a list of connected clients;
  • Broadcast transmission unit used to broadcast the coordinate points to the maintained client list after the 2D movement track recognition system detects the gesture signal.
  • the present invention can draw a displacement map of the movement trajectory of the watch by combining the accelerometer and gyroscope built in the smart watch, and further realizes the use of trajectory tracking gestures to control the target device.
  • the present invention may be a system, a method and/or a computer program product.
  • the computer program product may include a computer-readable storage medium loaded with computer-readable program instructions for enabling a processor to implement various aspects of the present invention.
  • the computer-readable storage medium may be a tangible device that holds and stores instructions used by the instruction execution device.
  • the computer-readable storage medium may include, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing, for example.
  • Non-exhaustive list of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) Or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, such as a printer with instructions stored thereon
  • RAM random access memory
  • ROM read-only memory
  • EPROM erasable programmable read-only memory
  • flash memory flash memory
  • SRAM static random access memory
  • CD-ROM compact disk read-only memory
  • DVD digital versatile disk
  • memory stick floppy disk
  • mechanical encoding device such as a printer with instructions stored thereon

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Abstract

一种基于智能手表的2D移动轨迹识别方法和装置。该方法包括：获取智能手表的加速度计信号数据以及陀螺仪信号数据；利用所述加速度计信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正；利用校正后的陀螺仪信号数据计算智能手表的角度值信息并估计坐标点。利用内置于智能手表的加速度计和陀螺仪，能够进行精确地估计智能手表的运动轨迹。

Description

一种基于智能手表的2D移动轨迹识别方法和系统 技术领域
本发明涉及智能设备交互技术领域，尤其涉及一种基于智能手表的2D移动轨迹识别方法和系统。
背景技术
目前，随着虚拟现实(VR)、人工智能技术逐渐受到追捧，智能手表、手环逐渐成为可穿戴领域的主流，但对于使用智能手表、手环的用户来说，智能手表的屏幕尺寸大小使得操作极其不便。与此同时，随着5G时代的来临，智能家居领域的市场前景更加广阔，目前控制智能家居的主要手段是通过手机进行控制，但用户在家中并不是随身携带手机的，用户和智能家居之间的交互体验不佳和操作复杂等问题也成为了热点问题。
因此，需要对现有技术改进，以进一步拓展智能手表的功能。
发明内容
本发明的目的在于克服上述现有技术的缺陷，提供一种基于智能手表的2D移动轨迹识别方法和系统，能够实现智能手表佩戴者的手势轨迹跟踪。
根据本发明的第一方面，提供一种基于智能手表的2D移动轨迹识别方法。该方法包括以下步骤：
获取智能手表的加速计信号数据以及陀螺仪信号数据；
利用所述加速度信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正；
利用校正后的陀螺仪信号数据计算智能手表的角度值信息并估计坐标点。
在一个实施例中，利用所述加速度信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正包括以下子步骤：
将加速度计信号数据的X、Y、Z轴数据分别记为a x、a y、a z，将陀螺仪信号数据的X、Y、Z轴数据分别记为g x、g y、g z；
计算加速度计信号数据的能量值大小e＝a x 2+a y 2+a z 2，初始化能量计数c＝0，并设置能量阈值大小e threshold以及能量计数阈值大小c threshold；
判断加速度计信号数据的能量值大小e是否小于等于能量阈值，若是，则更新能量计数信息c＝c+1，并判断能量计数c是否大于等于能量计数阈值c threshold，若是，则更新倾斜角度信息，表示为
Figure PCTCN2020113805-appb-000001
Figure PCTCN2020113805-appb-000002
利用更新的倾斜角度信息，对陀螺仪y轴和z轴角速度信号数据进行矫正，表示为
Figure PCTCN2020113805-appb-000003
其中，
Figure PCTCN2020113805-appb-000004
为矫正后的陀螺仪y轴数据，
Figure PCTCN2020113805-appb-000005
为矫正后的陀螺仪z轴数据。
在一个实施例中，所述能量计数阈值大小设置为c threshold＝f×0.1，所述能量阈值大小设置为e threshold＝0.04，其中f是数据的采样频率。
在一个实施例中，利用校正后的陀螺仪信号数据计算智能手表的角度值信息并估计坐标点包括以下子步骤：
设置陀螺仪信号数据两次采样时间间隔长度
Figure PCTCN2020113805-appb-000006
对矫正后的陀螺仪角速度信号数据在时间上积分，表示为θ x＝∫g xdt、
Figure PCTCN2020113805-appb-000007
其中，θ x为翻滚角，θ y为俯仰角，θ z为偏航角；
将二维垂直坐标系下的基向量设置为单位向量
Figure PCTCN2020113805-appb-000008
则当前坐标点为
Figure PCTCN2020113805-appb-000009
在一个实施例中，本发明的方法还包括：当获得估计的坐标点后，将坐标点广播给维护的客户端列表。
在一个实施例中，对于所获取的智能手表的加速计信号数据以及陀螺仪信号数据使用巴特沃滋滤波进行处理。
根据本发明的第二方面，提供一种基于智能手表的2D移动轨迹识别系统。该系统包括：用于获取智能手表的加速计信号数据以及陀螺仪信号数据的模块；用于利用所述加速度信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正的模块；用于利用校正后的陀螺 仪信号数据计算智能手表的角度值信息并估计坐标点的模块。
与现有技术相比，本发明的优点在于：能够在不改变智能手表的软/硬件的情况下拓展智能手表的功能，实现连续手势的轨迹跟踪记录。同时，通过与智能家居、电脑以及无人机等的配合，实现利用轨迹跟踪手势来对目标设备进行连续移动平滑操控，丰富了智能手表的应用场景。
附图说明
以下附图仅对本发明作示意性的说明和解释，并不用于限定本发明的范围，其中：
图1是根据本发明一个实施例的基于智能手表的2D移动轨迹识别方法的流程图；
图2是根据本发明一个实施例的陀螺仪坐标矫正流程图；
图3是根据本发明一个实施例的欧拉角的示意图。
具体实施方式
为了使本发明的目的、技术方案、设计方法及优点更加清楚明了，以下结合附图通过具体实施例对本发明进一步详细说明。应当理解，此处所描述的具体实施例仅用于解释本发明，并不用于限定本发明。
在本文示出和讨论的所有例子中，任何具体值应被解释为仅仅是示例性的，而不是作为限制。因此，示例性实施例的其它例子可以具有不同的值。
对于相关领域普通技术人员已知的技术、方法和设备可能不作详细讨论，但在适当情况下，所述技术、方法和设备应当被视为说明书的一部分。
参见图1所示，本发明实施例提供的基于智能手表的2D移动轨迹识别方法包括以下步骤：
步骤S1，采集智能手表的加速度计及陀螺仪传感器信号。
例如，利用智能手表上内置的加速度计和陀螺仪进行信号采集，获得智能手表的加速信号数据和陀螺仪信号数据。进一步地，为了消除噪声或异常数据，可对采集的信号滤波，例如使用巴特沃滋滤波处理采集的数据。
加速度计可以感知任意方向上的加速度，通过测量智能手表在某个轴向的受力情况来表征轴向的加速度大小和方向。陀螺仪通过测量三维坐标系内陀螺转子的垂直轴与智能手表之间的夹角，并计算角速度，通过夹角 和角速度来判别物体在三维空间的运动状态。以三轴加速度计和三轴陀螺仪为例，可获得加速度计和陀螺仪的x、y、z三轴的信号数据，由于智能手表与用户的手部紧贴，这些数据能够反映用户的手势运动情况。
步骤S2，利用加速度计信号数据估计倾斜角并校正陀螺仪的信号数据。
在此步骤中，利用加速度计信号数据对智能手表的倾斜角进行估计，并对陀螺仪信号数据进行矫正。
具体地，参见图2所示，利用加速度计数据对陀螺仪数据进行矫正包括以下步骤：
初始化倾斜角θ为0，此时cosθ、sinθ分别为1、0；
采集并使用巴特沃滋滤波后的加速度计X、Y、Z轴数据，记为a x、a y、a z，采集并使用巴特沃滋滤波后的陀螺仪X、Y、Z轴数据，记为g x、g y、g z，智能手表设备的传感器采样频率记为f(单位Hz)；
计算加速度计数据的能量值大小e＝a x 2+a y 2+a z 2，初始化能量计数c＝0，并设置能量阈值大小e threshold＝0.04以及能量计数阈值大小c threshold＝f×0.1，利用加速度计信号数据估计倾斜角θ。
判断能量值大小e是否小于等于能量阈值，若是，则更新能量计数信息：c＝c+1；
判断能量计数c是否大于等于能量计数阈值c threshold，若是，则更新倾斜角度θ信息：
Figure PCTCN2020113805-appb-000010
若否，则进入下一步；
利用倾斜角度θ信息，对陀螺仪y轴和z轴角速度信号数据进行矫正，表示为
Figure PCTCN2020113805-appb-000011
其中，
Figure PCTCN2020113805-appb-000012
为矫正后的陀螺仪y轴数据，
Figure PCTCN2020113805-appb-000013
为矫正后的陀螺仪z轴数据。
应理解的是，本发明实施例的能量阈值和计数阈值可根据应用场景等设置为合适的值，本发明对此不进行限制。
步骤S3，利用矫正后的陀螺仪信号数据计算智能手表当前状态下的角度值。
在此步骤中，利用矫正后的陀螺仪信号数据计算智能手表当前状态下的角度值信息(欧拉角)，并进而估算当前坐标点(x,y)，其中角度值信息参见图3所示，包括俯仰角、偏航角、翻滚角。
具体步骤包括：设置陀螺仪数据两次采样时间间隔长度
Figure PCTCN2020113805-appb-000014
对矫正后的陀螺仪角速度信号数据在时间上积分，表示为θ x＝∫g xdt、
Figure PCTCN2020113805-appb-000015
Figure PCTCN2020113805-appb-000016
其中，θ x为翻滚角，θ y为俯仰角，θ z为偏航角；基向量定义及坐标点估算，例如，将二维垂直坐标系下的基向量设置为单位向量
Figure PCTCN2020113805-appb-000017
估算当前坐标点，表示为
Figure PCTCN2020113805-appb-000018
Figure PCTCN2020113805-appb-000019
步骤S4，将结果发送给连接的客户端。
例如，利用蓝牙、Wi-Fi等协议将坐标点发送到连接本系统的客户端。具体步骤包括：在系统启动后开始监听使用蓝牙、Wi-Fi等协议连接本系统的请求，并维护处于连接状态的客户端列表；当2D移动轨迹识别系统检测到手势信号后，将坐标点广播给所维护的客户端列表。
相应地，本发明还提供一种基于智能手表的2D移动轨迹识别系统，用于实现上述方法的一个方面或多个方面。
例如，该系统包括：信号采集模块，其用于采集智能手表上的加速度计以及陀螺仪传感器的信号数据并使用巴特沃滋滤波处理采集的数据；信号矫正模块，其用于利用加速度计信号数据对智能手表的倾斜角进行估计，并对陀螺仪信号数据进行矫正；计算检测模块，其用于利用矫正后的陀螺仪信号数据计算智能手表当前状态下的角度值(俯仰角、偏航角、翻滚角)并估算当前坐标点(x,y)；数据传输模块，其用于利用蓝牙、Wi-Fi等协议将坐标点发送到连接本系统的客户端。
进一步地，所述信号矫正模块还包括：
数据采集记录单元，用于采集并使用巴特沃滋滤波后的加速度计X、Y、Z轴数据记为a x、a y、a z，采集并使用巴特沃滋滤波后的陀螺仪X、Y、Z轴数据记为g x、g y、g z；智能手表设备的传感器采样频率记为f；初始化倾斜角θ为0，此时cosθ、sinθ分别为1、0；
计算设置参数单元，用于计算加速度计数据的能量值大小e＝a x 2+a y 2+a z 2，初始化能量计数c＝0，并设置能量阈值大小e threshold＝0.04以及能量计数阈值大小c threshold＝f×0.1；
判断单元，用于判断能量值大小e是否小于等于能量阈值，若是，则更新能量计数信息：c＝c+1，并判断能量计数c是否大于等于能量计数 阈值c threshold,若是，则更新倾斜角度θ信息：
Figure PCTCN2020113805-appb-000020
Figure PCTCN2020113805-appb-000021
若否，则进入修正角速度单元；
修正角速度单元：用于利用倾斜角度θ信息，对陀螺仪y轴和z轴角速度信号数据进行矫正：
Figure PCTCN2020113805-appb-000022
Figure PCTCN2020113805-appb-000023
其中，
Figure PCTCN2020113805-appb-000024
为修正后的陀螺仪y轴数据，
Figure PCTCN2020113805-appb-000025
为矫正后的陀螺仪z轴数据。
进一步地，所述计算检测模块中还包括：
角速度积分单元：用于设置陀螺仪数据两次采样时间间隔长度
Figure PCTCN2020113805-appb-000026
对矫正后的陀螺仪角速度信号数据在时间上积分：θ x＝∫g xdt、
Figure PCTCN2020113805-appb-000027
Figure PCTCN2020113805-appb-000028
其中，θ x为翻滚角，θ y为俯仰角，θ z为偏航角；
坐标点计算单元：用于将二维垂直坐标系下的基向量设置为单位向量
Figure PCTCN2020113805-appb-000029
则当前坐标点为
Figure PCTCN2020113805-appb-000030
进一步地，所述数据传输模块中还包括：
监听协议单元：用于在系统启动后开始监听使用蓝牙、Wi-Fi等协议连接本系统的请求，并维护处于连接状态的客户端列表；
广播传输单元；用于当2D移动轨迹识别系统检测到手势信号后，将坐标点广播给所维护的客户端列表。
综上所述，本发明通过组合利用内置于智能手表的加速度计和陀螺仪能够绘制出手表的运动轨迹的位移图，并进而实现利用轨迹跟踪手势来对目标设备进行操控。
需要说明的是，虽然上文按照特定顺序描述了各个步骤，但是并不意味着必须按照上述特定顺序来执行各个步骤，实际上，这些步骤中的一些可以并发执行，甚至改变顺序，只要能够实现所需要的功能即可。
本发明可以是系统、方法和/或计算机程序产品。计算机程序产品可以包括计算机可读存储介质，其上载有用于使处理器实现本发明的各个方面的计算机可读程序指令。
计算机可读存储介质可以是保持和存储由指令执行设备使用的指令的有形设备。计算机可读存储介质例如可以包括但不限于电存储设备、磁存储设备、光存储设备、电磁存储设备、半导体存储设备或者上述的任意 合适的组合。计算机可读存储介质的更具体的例子(非穷举的列表)包括：便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、静态随机存取存储器(SRAM)、便携式压缩盘只读存储器(CD-ROM)、数字多功能盘(DVD)、记忆棒、软盘、机械编码设备、例如其上存储有指令的打孔卡或凹槽内凸起结构、以及上述的任意合适的组合。
以上已经描述了本发明的各实施例，上述说明是示例性的，并非穷尽性的，并且也不限于所披露的各实施例。在不偏离所说明的各实施例的范围和精神的情况下，对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。本文中所用术语的选择，旨在最好地解释各实施例的原理、实际应用或对市场中的技术改进，或者使本技术领域的其它普通技术人员能理解本文披露的各实施例。

Claims (10)

  1. 一种基于智能手表的2D移动轨迹识别方法，包括以下步骤：
    获取智能手表的加速计信号数据以及陀螺仪信号数据；
    利用所述加速度信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正；
    利用校正后的陀螺仪信号数据计算智能手表的角度值信息并估计坐标点。
  2. 根据权利要求1所述的基于智能手表的2D移动轨迹识别方法，其特征在于，利用所述加速度信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正包括以下子步骤：
    将加速度计信号数据的X、Y、Z轴数据分别记为a x、a y、a z，将陀螺仪信号数据的X、Y、Z轴数据分别记为g x、g y、g z；
    计算加速度计信号数据的能量值大小e＝a x 2+a y 2+a z 2，初始化能量计数c＝0，并设置能量阈值大小e threshold以及能量计数阈值大小c threshold；
    判断加速度计信号数据的能量值大小e是否小于等于能量阈值，若是，则更新能量计数信息c＝c+1，并判断能量计数c是否大于等于能量计数阈值c threshold，若是，则更新倾斜角度信息，表示为
    Figure PCTCN2020113805-appb-100001
    Figure PCTCN2020113805-appb-100002
    利用更新的倾斜角度信息，对陀螺仪y轴和z轴角速度信号数据进行矫正，表示为
    Figure PCTCN2020113805-appb-100003
    其中，
    Figure PCTCN2020113805-appb-100004
    为矫正后的陀螺仪y轴数据，
    Figure PCTCN2020113805-appb-100005
    为矫正后的陀螺仪z轴数据。
  3. 根据权利要求2所述的基于智能手表的2D移动轨迹识别方法，其特征在于，所述能量计数阈值大小设置为c threshold＝f×0.1，所述能量阈值大小设置为e threshold＝0.04，其中f是数据的采样频率。
  4. 根据权利要求1所述的基于智能手表的2D移动轨迹识别方法，其特征在于，利用校正后的陀螺仪信号数据计算智能手表的角度值信息并估计坐标点包括以下子步骤：
    设置陀螺仪信号数据两次采样时间间隔长度
    Figure PCTCN2020113805-appb-100006
    对矫正后的陀螺仪角速度信号数据在时间上积分，表示为θ x＝∫g xdt、
    Figure PCTCN2020113805-appb-100007
    其中，θ x为翻滚角，θ y为俯仰角，θ z为偏航角；
    将二维垂直坐标系下的基向量设置为单位向量
    Figure PCTCN2020113805-appb-100008
    则当前坐标点为
    Figure PCTCN2020113805-appb-100009
  5. 根据权利要求1所述的基于智能手表的2D移动轨迹识别方法，其特征在于，还包括：当获得估计的坐标点后，将坐标点广播给维护的客户端列表。
  6. 根据权利要求1所述的基于智能手表的2D移动轨迹识别方法，其特征在于，对于所获取的智能手表的加速计信号数据以及陀螺仪信号数据使用巴特沃滋滤波进行处理。
  7. 一种基于智能手表的2D移动轨迹识别系统，其特征在于，所述2D移动轨迹识别系统包括：
    用于获取智能手表的加速计信号数据以及陀螺仪信号数据的模块；
    用于利用所述加速度信号数据估计智能手表的倾斜角并利用该倾斜角对所述陀螺仪信号数据进行校正的模块；
    用于利用校正后的陀螺仪信号数据计算智能手表的角度值信息并估计坐标点的模块。
  8. 根据权利要求7所述的基于智能手表的2D移动轨迹识别系统，其特征在于，还包括：
    监听协议单元：用于监听连接至所述系统的请求，并维护处于连接状态的客户端列表；
    广播传输单元：用于将坐标点广播给所维护的客户端列表。
  9. 一种计算机可读存储介质，其上存储有计算机程序，其中，该程序被处理器执行时实现根据权利要求1至6中任一项所述方法的步骤。
  10. 一种计算机设备，包括存储器和处理器，在所述存储器上存储有能够在处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现权利要求1至6中任一项所述的方法的步骤。
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