WO2018137375A1 - 智能头盔摔倒检测方法及智能头盔 - Google Patents

智能头盔摔倒检测方法及智能头盔 Download PDF

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Publication number
WO2018137375A1
WO2018137375A1 PCT/CN2017/109449 CN2017109449W WO2018137375A1 WO 2018137375 A1 WO2018137375 A1 WO 2018137375A1 CN 2017109449 W CN2017109449 W CN 2017109449W WO 2018137375 A1 WO2018137375 A1 WO 2018137375A1
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WO
WIPO (PCT)
Prior art keywords
length
smart helmet
acceleration
threshold
preset condition
Prior art date
Application number
PCT/CN2017/109449
Other languages
English (en)
French (fr)
Inventor
郑波
叶永正
易湘棱
Original Assignee
深圳前海零距物联网科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 深圳前海零距物联网科技有限公司 filed Critical 深圳前海零距物联网科技有限公司
Priority to US16/461,759 priority Critical patent/US10897947B2/en
Publication of WO2018137375A1 publication Critical patent/WO2018137375A1/zh

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Classifications

    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/0406—Accessories for helmets
    • A42B3/0433—Detecting, signalling or lighting devices
    • A42B3/046—Means for detecting hazards or accidents
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/0406—Accessories for helmets
    • A42B3/0433—Detecting, signalling or lighting devices
    • A42B3/0453—Signalling devices, e.g. auxiliary brake or indicator lights
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/30—Mounting radio sets or communication systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P13/00—Indicating or recording presence, absence, or direction, of movement
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • G01P15/02—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration by making use of inertia forces using solid seismic masses
    • G01P15/08—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration by making use of inertia forces using solid seismic masses with conversion into electric or magnetic values
    • G01P15/0891—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration by making use of inertia forces using solid seismic masses with conversion into electric or magnetic values with indication of predetermined acceleration values
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • G01P15/18—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration in two or more dimensions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/14—Receivers specially adapted for specific applications
    • G01S19/17—Emergency applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
    • G08B21/0407—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis
    • G08B21/043—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis detecting an emergency event, e.g. a fall
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
    • G08B21/0438—Sensor means for detecting
    • G08B21/0446—Sensor means for detecting worn on the body to detect changes of posture, e.g. a fall, inclination, acceleration, gait
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
    • G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
    • G08B25/10—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using wireless transmission systems
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B3/00—Audible signalling systems; Audible personal calling systems
    • G08B3/10—Audible signalling systems; Audible personal calling systems using electric transmission; using electromagnetic transmission
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B5/00—Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied
    • G08B5/22—Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied using electric transmission; using electromagnetic transmission
    • G08B5/36—Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied using electric transmission; using electromagnetic transmission using visible light sources

Definitions

  • the present invention relates to the field of sports protection, and in particular, to a smart helmet fall detection method and a smart helmet.
  • Cycling is an outdoor sport that people have always been keen on. During the riding process, the most likely accident is to fall and fall to the ground after being hit. If the impact is serious, it may be unconscious or unable to move. Help, lose valuable rescue time, especially when the accident occurs in remote mountainous areas, more dangerous. Therefore, in the event of a fall, if the relevant personnel can be notified and rescued, the damage caused by the fall will be greatly reduced, so it is necessary to detect and alarm the fall event.
  • Cycling is an outdoor sport that people have always been keen on. During the riding process, the most likely accident is to fall and fall to the ground after being hit. If the impact is serious, it may be unconscious or unable to move. Help, lose valuable rescue time, especially when the accident occurs in remote mountainous areas, more dangerous. Therefore, in the event of a fall, if the relevant personnel can be notified and rescued, the damage caused by the fall will be greatly reduced, so it is necessary to detect and alarm the fall event.
  • a smart helmet fall detection method includes the following steps: monitoring a triaxial acceleration according to a preset monitoring frequency; calculating the triaxial acceleration vector sum, and according to the acceleration vector and whether the first preset condition is met And determining whether a free fall event occurs; determining whether an impact event occurs according to whether the acceleration of any one of the three axes satisfies a second preset condition; whether the amount of acceleration change detected according to each axis satisfies a third preset condition And determining whether a stationary event occurs; and generating a distress signal according to the stationary event meeting the fourth preset condition.
  • the smart helmet fall detection method further includes: comparing the impact event and The inter-turn interval of the free fall event is longer than a predetermined failure length; and the step of determining whether a stationary event occurs according to the comparison result that the inter-turn interval is less than or equal to the failure length, or according to the The comparison result that the interval is greater than the failure length returns the step of monitoring the triaxial acceleration.
  • the first preset condition is that the acceleration vector sum continues to be less than the first threshold and continues to exceed the first length
  • the second preset condition is any one of the The acceleration of the shaft continues to be greater than the second threshold and continues for more than the second length
  • the third preset condition is that the amount of acceleration change continues to be less than the third threshold and continues for longer than the third length
  • the fourth The preset condition is that the stationary event occurs within a fourth length from the occurrence of the impact event, wherein the third length is shorter than the fourth length.
  • the first threshold is 0.3 to 0.6 g
  • the first length is 400 ms to 500 ms
  • the second threshold is 1.5 to 2 g
  • the second length is
  • the third threshold is 0.3g ⁇ 0.6g
  • the third length is 8 ⁇ 15s
  • the fourth length is different from the third length by 2 ⁇ 5s.
  • the first threshold is 0.54 g
  • the first length is 450 ms
  • the second threshold is 1.992 g
  • the second length is 400 ms
  • the third The threshold is 0.5 g
  • the third length is 1 Is
  • the fourth length is 15 s.
  • the fall detection method further includes: detecting whether the static event continues to occur; and generating an alarm release signal if the static event is not detected three times in succession.
  • a smart helmet comprising: a three-axis acceleration sensor for detecting three-axis acceleration; and a controller, configured to: monitor three-axis acceleration according to a preset monitoring frequency; calculate the three-axis acceleration a vector sum, and determining whether a free fall event occurs according to the acceleration vector and whether the first preset condition is satisfied; determining whether an impact event occurs according to whether the acceleration of any one of the three axes satisfies the second preset condition; Determining whether a stationary event occurs according to whether the amount of acceleration change detected by each axis satisfies a third preset condition; and generating a distress signal according to the fourth preset condition being satisfied according to the stationary event.
  • the first preset condition is that the acceleration vector sum continues to be less than the first threshold and continues to exceed the first length
  • the second preset condition is any one of the The acceleration of the shaft continues to be greater than the second threshold and continues for longer than the second length
  • the third predetermined condition being the amount of acceleration change Sustaining less than the third threshold and continuing for more than the third length
  • the fourth predetermined condition is that the quiescent event occurs within a fourth length from the occurrence of the impact event, wherein the third ⁇ The length is shorter than the fourth length.
  • the smart helmet further includes a warning light, and the warning light is used to initiate a fall warning illumination mode.
  • the smart helmet further includes a GPS positioning module and a wireless communication module, where the GPS positioning module is configured to send current geographic location information to the controller, where the wireless communication module is used to The help information is sent to the preset number by the mobile terminal associated with the smart helmet, and the help information carries the current geographic location information.
  • the smart helmet fall detection method and the smart helmet provided by the invention measure the acceleration by installing a three-axis acceleration sensor on the smart helmet, and determine whether a fall event occurs by analyzing the change of the acceleration. And according to the fall event to make an alarm, so as to solve the problem of fall detection and call for help during the ride.
  • FIG. 1 is a schematic flow chart of a smart helmet fall detection method according to a first embodiment of the present invention
  • step S4 of the smart helmet fall detection method according to the first embodiment of the present invention
  • FIG 3 is a schematic structural view of a smart helmet according to a second embodiment of the present invention.
  • a smart helmet fall detection method includes steps S1 to S5. [0024] Step S1, monitoring a triaxial acceleration according to a preset monitoring frequency.
  • Step S2 calculating the triaxial acceleration vector sum, and determining whether a free fall event occurs according to whether the acceleration vector satisfies the first preset condition.
  • Step S3 Determine whether an impact event occurs according to whether the acceleration of any one of the three axes satisfies the second preset condition.
  • Step S4 determining whether a stationary event occurs according to whether the amount of acceleration change detected by each axis satisfies a third preset condition.
  • Step S5 generating a distress signal according to the stationary event meeting the fourth preset condition.
  • the triaxial acceleration sensor is initialized to correctly detect the fall event.
  • step S1 the controller monitors the three-axis acceleration according to a certain frequency, and the monitoring frequency thereof may be the same as or different from the output frequency of the three-axis acceleration sensor.
  • step S2 the controller waits for a free fall event that satisfies the first preset condition
  • the first preset condition is that the acceleration vector and the duration are less than the first threshold and the duration exceeds the first length
  • the first threshold and the first length are determined according to the riding characteristics.
  • the first threshold (Thresh-FF) is set to 0.3 to 0.6 g according to the height range of the rider of the rider, and g represents the acceleration of gravity.
  • set the first length (Ti me-FF) to 400ms ⁇ 500ms.
  • the first threshold is 0.54 g
  • the first length is 45 0 ms.
  • a free fall event occurs when the acceleration vector sum continues to be less than the first threshold and continues for more than the first length. If the free fall event has not occurred, return to step S1.
  • step S3 the controller waits for an impact event that meets the second preset condition to occur, and the second preset condition is that the acceleration of the arbitrary one axis continues to be greater than the second threshold and continues to exceed the second length for the daytime.
  • the specific second threshold and the second length are determined according to the riding characteristics. This embodiment is based on the range of riding speed of the rider
  • the second threshold (Thresh-Activity) is set to 1.5 to 2 g
  • the second length (Time-Act) is set to 300 to 450 ms.
  • the second threshold is 1.992 g
  • the second length is 400 ms.
  • step S1 When any one of the axial accelerations (the impact may occur in either direction) is greater than the second threshold and continues for more than the second length, the rider is considered to have hit the ground and an impact event occurs. If the impact event has not occurred, the process returns to step S1.
  • step S4 the controller waits for a stationary event that meets the third preset condition to occur, and the third preset condition is that the acceleration change amount continues to be less than the third threshold and continues for more than the third length.
  • the third threshold (Thresh-Inact) is set to 0.3 g to 0.6 g
  • the third length (Time-Inact) is set to 8 to 15 s.
  • the third threshold is 0.5 g.
  • the third length is l ls.
  • a stationary event occurs when the amount of change in the acceleration of each axis is less than the third threshold and continues for more than the third length.
  • the amount of change refers to the difference between the maximum value and the minimum value detected in the range of at least the third length. In the third length range, the rider has almost no movement, indicating that it is highly likely to be in a coma or unable to move. The situation.
  • step S5 it is considered that the rider hits the ground after falling at the speed of riding, and does not immediately occur at least for a third period of time, and a certain length of rolling occurs to a large extent. It will be still, therefore, the fourth preset condition needs to be set to make a reasonable judgment.
  • the fourth preset condition is specifically adding a buffering gauge after the impact event occurs, that is, if the static event occurs within a fourth length from the occurrence of the impact event, Free fall-impact-stationary events are generated, the rider has fallen, and a distress signal is required.
  • the distress signal is sent by the controller to the corresponding rescue module to send out a control signal, and the form of the distress signal is not limited, for example, a distressing sound and a light prompt are issued, and the mobile phone sends a help message or calls for a call.
  • the fourth length is different from the third length by 2 to 5 seconds. Preferably, the fourth length is 15 s.
  • steps S41 to S42 are further included in step S4.
  • Step S41 comparing the inter-turn interval of the impact event and the free fall event with a predetermined failure length.
  • Step S42 performing the step of determining whether a stationary event occurs according to the comparison result that the inter-turn interval is less than or equal to the failure length, or according to the comparison that the inter-turn interval is greater than the failure length The result is returned to the step of monitoring the triaxial acceleration.
  • the failure length is set, for example, 200 ms, that is, the inter-turn interval between the impact event and the free fall event is less than 200 ms, indicating that there is a strong correlation between the free fall and the impact, and the waiting event may be awaited.
  • More than 200ms means that there is only a free fall but no impact, then it can be considered that there is no correlation between the free fall and the impact, and the acceleration is continuously monitored.
  • the distress signal is sent, it is also detected whether the stationary event continues to occur; and if the static event is not detected three times in succession, the person indicating that the fall can be active, generating an alarm release signal, The axis sensor continues to monitor after initialization.
  • the smart helmet fall detection method measures the acceleration by installing a three-axis acceleration sensor on the smart helmet, and determines whether the occurrence occurs by analyzing the change of the acceleration of the fall event during riding.
  • the fall event and the alarm according to the fall event which solves the problem of fall detection and call for help during the ride.
  • a smart helmet 100 includes a three-axis acceleration sensor 10 for detecting triaxial acceleration, and a controller 20 for: Monitoring a triaxial acceleration according to a preset monitoring frequency; calculating the triaxial acceleration vector sum, and determining whether a free fall event occurs according to the acceleration vector and whether the first preset condition is satisfied; according to any one of the three axes Whether the acceleration of the axis satisfies the second preset condition to determine whether an impact event occurs; determining whether a stationary event occurs according to whether the amount of acceleration change detected by each axis satisfies a third preset condition; and satisfying the fourth event according to the stationary event
  • the preset condition generates a distress signal.
  • the first preset condition is that the acceleration vector sum continues to be less than the first threshold and continues to exceed the first length
  • the second preset condition is that the acceleration of the arbitrary axis continues to be greater than a second threshold value that lasts longer than the second ⁇ length
  • the third preset condition is that the acceleration change amount continues to be less than the third threshold value and continues to exceed the third ⁇ length
  • the fourth preset condition is The stationary event occurs within a fourth length from the occurrence of the impact event, wherein the third length is shorter than the fourth length.
  • the first threshold is 0.3 to 0.6 g, the first length is 400 ms to 500 ms; the second threshold is 1.5 to 2 g, and the second length is 300 ms to 450 ms;
  • the third threshold is 0.3g ⁇ 0.6g, and the third length is 8 ⁇ 15s; the fourth length is different from the third length by 2 ⁇ 5s.
  • the first threshold is 0.54 g, the first length is 450 ms, the second threshold is 1.992 g, the second length is 400 ms, and the third threshold is 0.5 g.
  • the third length is l is , and the fourth length is 15 s.
  • the controller 20 is further configured to compare the inter-turn interval of the impact event and the free fall event with a predetermined failure length; and compare the length of the failure according to the inter-turn interval a step of performing the step of determining whether a stationary event occurs, or returning the monitoring triaxial acceleration according to a comparison result that the inter-turn interval is greater than the failure length, and detecting whether the stationary event continues to occur; And if the stationary event is not detected three times in succession, an alarm release signal is generated to stop the distress signal.
  • the smart helmet 100 further includes a warning light 30, and the warning light 30 is used to initiate a fall warning lighting mode, such as emitting a strobe, stroboscopic, or SOS distress mode.
  • a fall warning lighting mode such as emitting a strobe, stroboscopic, or SOS distress mode.
  • the smart helmet 100 further includes a GPS positioning module 40 and a wireless communication module 41, wherein the GPS positioning module 40 is configured to send current geographic location information to the controller 20, and the wireless communication module 41 passes through The mobile terminal associated with the smart helmet sends the help information to the preset number, and the help information carries the current geographic location information.
  • the smart helmet 100 can be connected through a wireless communication module 41, such as a Bluetooth module, and a mobile phone, and the control signal sent by the controller 20 controls the mobile phone to a preset number (such as an emergency contact registered by a rider or an emergency center).
  • the number sends a distress message, and the distress message includes a help message or a call for help.
  • the smart helmet 100 further includes a speaker 50 for emitting an alarm sound.
  • the smart helmet provided in the embodiment of the present invention measures the acceleration by installing a three-axis acceleration sensor on the smart helmet, and determines whether a fall event occurs by analyzing the change of the acceleration, and performs an alarm according to the fall event. Therefore, the problem of fall detection and call for help during riding is solved in a targeted manner.

Abstract

一种智能头盔摔倒检测方法以及智能头盔（100）。摔倒检测方法包括以下步骤：系统初始化，自由落体判定（S2），撞击判定（S3），静止判定（S4），以及根据静止事件发生在自撞击事件发生后的第四时长内的检测结果生成求救信号（S5）。智能头盔（100）包括三轴加速度传感器（10）及控制器（20）。智能头盔摔倒检测方法及智能头盔（100）通过在智能头盔（100）上安装三轴加速度传感器（10）测量加速度，并通过分析加速度的变化情况来判断是否发生骑行摔倒事件，并根据摔倒事件进行报警，从而有针对性地解决了骑行过程中摔倒检测及呼救的问题。

Description

智能头盔摔倒检测方法及智能头盔
技术领域
[0001] 本发明涉及运动保护领域， 尤其涉及智能头盔摔倒检测方法及智能头盔。
背景技术
[0002] 骑行运动是人们一贯热衷的户外运动， 在骑行过程中， 最容易发生的事故是跌 落和受到撞击后摔倒在地， 撞击严重吋很可能昏迷不醒或者无法动弹， 从而无 法求助， 失去宝贵的抢救吋间， 尤其当事故发生在偏远山地吋， 更加危险。 因 此当出现跌倒情况吋， 如果能够及吋通知相关人员进行救助， 将会大大地减轻 由于跌倒而造成的危害， 因此有必要对摔倒事件进行检测和报警。
[0003] 骑行运动是人们一贯热衷的户外运动， 在骑行过程中， 最容易发生的事故是跌 落和受到撞击后摔倒在地， 撞击严重吋很可能昏迷不醒或者无法动弹， 从而无 法求助， 失去宝贵的抢救吋间， 尤其当事故发生在偏远山地吋， 更加危险。 因 此当出现跌倒情况吋， 如果能够及吋通知相关人员进行救助， 将会大大地减轻 由于跌倒而造成的危害， 因此有必要对摔倒事件进行检测和报警
技术问题
[0004] 本发明的目的在于， 解决如何检测骑行过程中发生摔倒事件的问题。
问题的解决方案
技术解决方案
[0005] 本发明的目的是采用以下技术方案来实现的。
[0006] 一种智能头盔摔倒检测方法， 包括以下步骤： 按照预设的监测频率监测三轴加 速度； 计算所述三轴加速度矢量和， 并根据所述加速度矢量和是否满足第一预 设条件而判断是否发生自由落体事件； 根据所述三轴中任意一轴的加速度是否 满足第二预设条件而判断是否发生撞击事件； 根据每一轴检测到的加速度变化 量是否满足第三预设条件而判断是否发生静止事件； 以及根据所述静止事件满 足第四预设条件而生成求救信号。
[0007] 在一种实施方式中， 所述智能头盔摔倒检测方法还包括： 比较所述撞击事件和 所述自由落体事件的吋间间隔与预定的失效吋长； 以及根据所述吋间间隔小于 或等于所述失效吋长的比较结果执行所述判断是否发生静止事件的步骤， 或者 根据所述吋间间隔大于所述失效吋长的比较结果返回所述监测三轴加速度的步 骤。
[0008] 在一种实施方式中， 所述第一预设条件为所述加速度矢量和持续小于第一阈值 且持续吋间超过第一吋长， 所述第二预设条件为所述任意一轴的加速度持续大 于第二阈值且持续吋间超过第二吋长， 所述第三预设条件为所述加速度变化量 持续小于第三阈值且持续吋间超过第三吋长， 所述第四预设条件为所述静止事 件发生在自所述撞击事件发生后的第四吋长内， 其中， 所述第三吋长短于所述 第四吋长。
[0009] 在一种实施方式中， ， 所述第一阈值为 0.3〜0.6g， 所述第一吋长为 400ms〜500 ms ; 所述第二阈值为 1.5〜2g， 所述第二吋长为 300ms〜450ms ; 所述第三阈值为 0.3g〜0.6g， 所述第三吋长为 8〜15s ; 所述第四吋长与所述第三吋长相差 2〜5s。
[0010] 在一种实施方式中， 所述第一阈值为 0.54g， 所述第一吋长为 450ms， 所述第二 阈值为 1.992g， 所述第二吋长为 400ms， 所述第三阈值为 0.5g， 所述第三吋长为 1 Is , 所述第四吋长为 15s。
[0011] 在一种实施方式中， 所述摔倒检测方法还包括： 检测是否持续发生所述静止事 件； 以及若连续三次未检测到所述静止事件， 生成警报解除信号。
[0012] 一种智能头盔， 所述智能头盔包括： 三轴加速度传感器， 用于检测三轴加速度 ； 以及控制器， 用于： 按照预设的监测频率监测三轴加速度； 计算所述三轴加 速度矢量和， 并根据所述加速度矢量和是否满足第一预设条件而判断是否发生 自由落体事件； 根据所述三轴中任意一轴的加速度是否满足第二预设条件而判 断是否发生撞击事件； 根据每一轴检测到的加速度变化量是否满足第三预设条 件而判断是否发生静止事件； 以及根据所述静止事件满足第四预设条件而生成 求救信号。
[0013] 在一种实施方式中， 所述第一预设条件为所述加速度矢量和持续小于第一阈值 且持续吋间超过第一吋长， 所述第二预设条件为所述任意一轴的加速度持续大 于第二阈值且持续吋间超过第二吋长， 所述第三预设条件为所述加速度变化量 持续小于第三阈值且持续吋间超过第三吋长， 所述第四预设条件为所述静止事 件发生在自所述撞击事件发生后的第四吋长内， 其中， 所述第三吋长短于所述 第四吋长。
[0014] 在一种实施方式中， 所述智能头盔进一步包括警示灯， 所述警示灯用于幵启摔 倒警示发光模式。
[0015] 在一种实施方式中， 所述智能头盔进一步包括 GPS定位模块和无线通信模块， 所述 GPS定位模块用于向所述控制器发送当前的地理位置信息， 所述无线通信模 块用于通过与所述智能头盔相关联的移动终端向预设号码发送求救信息， 所述 求救信息携带所述当前地理位置信息。
发明的有益效果
有益效果
[0016] 相较于现有技术， 本发明提供的智能头盔摔倒检测方法及智能头盔通过在智能 头盔上安装三轴加速度传感器测量加速度， 并通过分析加速度的变化情况来判 断是否发生摔倒事件， 并根据摔倒事件进行报警， 从而有针对性地解决了骑行 过程中摔倒检测及呼救的问题。
[0017] 上述说明仅是本发明技术方案的概述， 为了能够更清楚了解本发明的技术手段 ， 而可依照说明书的内容予以实施， 并且为了让本发明的上述和其他目的、 特 征和优点能够更明显易懂， 以下特举较佳实施例， 并配合附图， 详细说明如下 对附图的简要说明
附图说明
[0018] 图 1是本发明第一实施例提供的智能头盔摔倒检测方法的流程示意图；
[0019] 图 2是本发明第一实施例提供的智能头盔摔倒检测方法的步骤 S4的一种实施方 式的流程示意图；
[0020] 图 3是本发明第二实施例提供的智能头盔的结构示意图。
实施该发明的最佳实施例
本发明的最佳实施方式 [0021] 下面将结合本发明实施例中的附图， 对本发明实施例中的技术方案进行清楚、 完整地描述， 显然， 所描述的实施例仅仅是本发明一部分实施例， 而不是全部 的实施例。 基于本发明中的实施例， 本领域普通技术人员在没有做出创造性劳 动前提下所获得的所有其他实施例， 都属于本发明保护的范围。
[0022] 第一实施例
[0023] 请参阅图 1， 本发明第一实施例提供的智能头盔摔倒检测方法包括步骤 S1〜S5 [0024] 步骤 Sl， 按照预设的监测频率监测三轴加速度。
[0025] 步骤 S2， 计算所述三轴加速度矢量和， 并根据所述加速度矢量和是否满足第一 预设条件而判断是否发生自由落体事件。
[0026] 步骤 S3， 根据所述三轴中任意一轴的加速度是否满足第二预设条件而判断是否 发生撞击事件。
[0027] 步骤 S4， 根据每一轴检测到的加速度变化量是否满足第三预设条件而判断是否 发生静止事件。
[0028] 步骤 S5， 根据所述静止事件满足第四预设条件而生成求救信号。
[0029] 在步骤 S1之前， 优选地， 对三轴加速度传感器初始化以正确地检测摔倒事件。
在步骤 S1中， 控制器按照一定频率监测三轴加速度， 其监测频率可以和三轴加 速度传感器的输出频率相同， 也可以不同。
[0030] 在步骤 S2中， 控制器等待满足第一预设条件的自由落体事件发生， 第一预设条 件为所述加速度矢量和持续小于第一阈值且持续吋间超过第一吋长， 具体的第 一阈值和第一吋长根据骑行特点制定， 本实施例根据骑行人员的在骑行吋的高 度范围把第一阈值 (Thresh-FF)设为 0.3〜0.6g， g表示重力加速度， 把第一吋长 (Ti me-FF)设为 400ms〜500ms。 优选地， 所述第一阈值为 0.54g， 所述第一吋长为 45 0ms。 当加速度矢量和持续小于第一阈值且持续吋间超过第一吋长， 发生自由落 体事件。 若未发生自由落体事件， 则返回步骤 Sl。
[0031] 在步骤 S3中， 控制器等待满足第二预设条件的撞击事件发生， 第二预设条件为 所述任意一轴的加速度持续大于第二阈值且持续吋间超过第二吋长， 具体的第 二阈值和第二吋长根据骑行特点制定。 本实施例根据骑行人员的骑行速度范围 把第二阈值 (Thresh- Act)设为 1.5〜2g， 把第二吋长 (Time-Act)设为 300〜450ms。 优选地， 所述第二阈值为 1.992g， 所述第二吋长为 400ms。 当任意一个轴加速度 ( 撞击可能发生在任意一个方向)大于第二阈值且持续吋间超过第二吋长吋， 认为 骑行人员撞击到地面， 发生撞击事件。 若未发生撞击事件， 则返回步骤 Sl。
[0032] 在步骤 S4中， 控制器等待满足第三预设条件的静止事件发生， 第三预设条件为 所述加速度变化量持续小于第三阈值且持续吋间超过第三吋长。 本实施例将第 三阈值 (Thresh-Inact)设为 0.3g〜0.6g， 把第三吋长 (Time-Inact)设为 8〜15s， 优选 地， 所述第三阈值为 0.5g， 所述第三吋长为 l ls。 当各个轴加速度变化量小于第 三阈值且持续吋间超过第三吋长吋， 发生静止事件。 变化量是指至少第三吋长 范围内所检测到的最大值和最小值之间的差值， 在第三吋长范围内骑行人员几 乎没有动， 表示其极有可能处于昏迷或者无法动弹的情形。
[0033] 在步骤 S5中， 考虑到骑行人员在以骑行的速度发生摔倒后撞击地面不会立即发 生至少第三吋长内的静止， 很大程度上会发生一定吋长的滚动才会静止， 因此 ， 需要设置第四预设条件来进行合理判断。 在本实施例中， 第四预设条件具体 是在所述撞击事件发生后增加一段缓冲计吋， 即如果所述静止事件发生在自所 述撞击事件发生后的第四吋长内， 则表示自由落体-撞击-静止三种事件均产生， 骑行人员已摔倒， 需要发出求救信号。 求救信号由控制器向相应的求救模块发 出控制信号来发出， 求救信号的形式不限， 例如发出求救声音和灯光提示、 上 报手机由手机发出求救短信或拨打求救电话等。 本实施例中， 第四吋长与所述 第三吋长相差 2〜5s。 优选地， 第四吋长为 15s。
[0034] 如果上述几个事件均不符合相应的预设条件， 则表示摔倒事件不成立， 继续监 测三轴加速度。
[0035] 为了进一步精确判断骑行当中自由落体事件和撞击事件之间的关联性， 优选的
， 请参阅图 2， 在步骤 S4中还进一步包括步骤 S41〜S42。
[0036] 步骤 S41， 比较所述撞击事件和所述自由落体事件的吋间间隔与预定的失效吋 长。
[0037] 步骤 S42， 根据所述吋间间隔小于或等于所述失效吋长的比较结果执行所述判 断是否发生静止事件的步骤， 或者根据所述吋间间隔大于所述失效吋长的比较 结果返回所述监测三轴加速度的步骤。
[0038] 在步骤 S41中， 设置失效吋长， 例如 200ms， 即撞击事件和自由落体事件之间的 吋间间隔小于 200ms， 则表示自由落体和撞击之间具有强关联， 可以等待静止事 件的发生。 超过 200ms表示只有自由落体但是没有撞击， 则可以认为自由落体和 撞击之间无关联， 继续监测加速度。
[0039] 优选的， 在发出求救信号后， 还可以检测是否持续发生所述静止事件； 以及若 连续三次未检测到所述静止事件， 表示摔倒的人员可以活动， 生成警报解除信 号， 对三轴传感器初始化后继续监测。
[0040] 综上， 本发明实施例中提供的智能头盔摔倒检测方法通过在智能头盔上安装三 轴加速度传感器测量加速度， 并通过分析骑行中摔倒事件的加速度的变化情况 来判断是否发生摔倒事件， 并根据摔倒事件进行报警， 从而有针对性地解决了 骑行过程中摔倒检测及呼救的问题。
[0041] 第二实施例
[0042] 请参阅图 3， 本发明第二实施例提供的智能头盔 100包括三轴加速度传感器 10和 控制器 20， 该三轴加速度传感器 10用于检测三轴加速度， 该控制器 20用于： 按 照预设的监测频率监测三轴加速度； 计算所述三轴加速度矢量和， 并根据所述 加速度矢量和是否满足第一预设条件而判断是否发生自由落体事件； 根据所述 三轴中任意一轴的加速度是否满足第二预设条件而判断是否发生撞击事件； 根 据每一轴检测到的加速度变化量是否满足第三预设条件而判断是否发生静止事 件； 以及根据所述静止事件满足第四预设条件生成求救信号。
[0043] 其中， 所述第一预设条件为所述加速度矢量和持续小于第一阈值且持续吋间超 过第一吋长， 所述第二预设条件为所述任意一轴的加速度持续大于第二阈值且 持续吋间超过第二吋长， 所述第三预设条件为所述加速度变化量持续小于第三 阈值且持续吋间超过第三吋长， 所述第四预设条件为所述静止事件发生在自所 述撞击事件发生后的第四吋长内， 其中， 所述第三吋长短于所述第四吋长。
[0044] 其中， 所述第一阈值为 0.3〜0.6g， 所述第一吋长为 400ms〜500ms; 所述第二 阈值为 1.5〜2g， 所述第二吋长为 300ms〜450ms; 所述第三阈值为 0.3g〜0.6g， 所述第三吋长为 8〜15s ; 所述第四吋长与所述第三吋长相差 2〜5s。 [0045] 优选的， 所述第一阈值为 0.54g， 所述第一吋长为 450ms， 所述第二阈值为 1.992 g， 所述第二吋长为 400ms， 所述第三阈值为 0.5g， 所述第三吋长为 l is , 所述第 四吋长为 15s。
[0046] 所述控制器 20还用于比较所述撞击事件和所述自由落体事件的吋间间隔与预定 的失效吋长； 以及根据所述吋间间隔小于或等于所述失效吋长的比较结果执行 所述判断是否发生静止事件的步骤， 或者根据所述吋间间隔大于所述失效吋长 的比较结果返回所述监测三轴加速度的步骤， 以及用于检测是否持续发生所述 静止事件； 以及若连续三次未检测到所述静止事件， 生成警报解除信号以停止 该求救信号。
[0047] 所述智能头盔 100进一步包括警示灯 30， 所述警示灯 30用于幵启摔倒警示发光 模式， 例如发出爆闪、 频闪、 或者 SOS求救模式等。
[0048] 所述智能头盔 100进一步包括 GPS定位模块 40和无线通信模块 41， 所述 GPS定位 模块 40用于向所述控制器 20发送当前的地理位置信息， 所述无线通信模块 41通 过与所述智能头盔相关联的移动终端向预设号码发送求救信息， 所述求救信息 携带所述当前地理位置信息。
[0049] 智能头盔 100可以通过无线通信模块 41， 例如蓝牙模块， 和手机进行连接， 控 制器 20发出的控制信号控制手机向预设的号码 (例如骑行人员登记的紧急联系人 或者急救中心的号码)发送求救信息， 求救信息包括求救短信或者求救电话。
[0050] 所述智能头盔 100进一步包括扬声器 50， 所述扬声器 50用于发出报警声音。
[0051] 综上， 本发明实施例中提供的智能头盔通过在智能头盔上安装三轴加速度传感 器测量加速度， 并通过分析加速度的变化情况来判断是否发生摔倒事件， 并根 据摔倒事件进行报警， 从而有针对性地解决了骑行过程中摔倒检测及呼救的问 题。
[0052] 以上所述实施例仅表达了本发明的几种实施方式， 其描述较为具体和详细， 但 并不能因此而理解为对本发明专利范围的限制。 应当指出的是， 对于本领域的 普通技术人员来说， 在不脱离本发明构思的前提下， 还可以做出若干变形和改 进， 这些都属于本发明的保护范围。 因此， 本发明专利的保护范围应以所附权 利要求为准。

Claims

权利要求书
[权利要求 1] 一种智能头盔摔倒检测方法， 其特征在于， 包括以下步骤： 按照预设 的监测频率监测三轴加速度； 计算所述三轴加速度矢量和， 并根据所 述加速度矢量和是否满足第一预设条件而判断是否发生自由落体事件 ； 根据所述三轴中任意一轴的加速度是否满足第二预设条件而判断是 否发生撞击事件； 根据每一轴检测到的加速度变化量是否满足第三预 设条件而判断是否发生静止事件； 以及根据所述静止事件满足第四预 设条件而生成求救信号。
[权利要求 2] 如权利要求 1所述的智能头盔摔倒检测方法， 其特征在于， 所述智能 头盔摔倒检测方法还包括： 比较所述撞击事件和所述自由落体事件的 吋间间隔与预定的失效吋长； 以及根据所述吋间间隔小于或等于所述 失效吋长的比较结果执行所述判断是否发生静止事件的步骤， 或者根 据所述吋间间隔大于所述失效吋长的比较结果返回所述监测三轴加速 度的步骤。
[权利要求 3] 如权利要求 1所述的智能头盔摔倒检测方法， 其特征在于， 所述第一 预设条件为所述加速度矢量和持续小于第一阈值且持续吋间超过第一 吋长， 所述第二预设条件为所述任意一轴的加速度持续大于第二阈值 且持续吋间超过第二吋长， 所述第三预设条件为所述加速度变化量持 续小于第三阈值且持续吋间超过第三吋长， 所述第四预设条件为所述 静止事件发生在自所述撞击事件发生后的第四吋长内， 其中， 所述第 三吋长短于所述第四吋长。
[权利要求 4] 如权利要求 3所述的智能头盔摔倒检测方法， 其特征在于， 所述第一 阈值为 0.3〜0.6g， 所述第一吋长为 400ms〜500ms ; 所述第二阈值为 1. 5〜2g， 所述第二吋长为 300ms〜450ms ; 所述第三阈值为 0.3g〜0.6g ， 所述第三吋长为 8〜15s; 所述第四吋长与所述第三吋长相差 2〜5s
[权利要求 5] 如权利要求 4所述的智能头盔摔倒检测方法， 其特征在于， 所述第一 阈值为 0.54g， 所述第一吋长为 450ms， 所述第二阈值为 1.992g， 所述 第二吋长为 400ms， 所述第三阈值为 0.5g， 所述第三吋长为 l is, 所述 第四吋长为 15s。
如权利要求 1所述的智能头盔摔倒检测方法， 其特征在于， 所述摔倒 检测方法还包括： 检测是否持续发生所述静止事件； 以及若连续三次 未检测到所述静止事件， 生成警报解除信号以停止所述求救信号。 一种智能头盔， 其特征在于， 所述智能头盔包括： 三轴加速度传感器 ， 用于检测三轴加速度； 以及， 控制器， 用于： 按照预设的监测频率 监测三轴加速度； 计算所述三轴加速度矢量和， 并根据所述加速度矢 量和是否满足第一预设条件而判断是否发生自由落体事件； 根据所述 三轴中任意一轴的加速度是否满足第二预设条件而判断是否发生撞击 事件； 根据每一轴检测到的加速度变化量是否满足第三预设条件而判 断是否发生静止事件； 以及根据所述静止事件满足第四预设条件而生 成求救信号。
如权利要求 7所述的智能头盔， 其特征在于， 所述第一预设条件为所 述加速度矢量和持续小于第一阈值且持续吋间超过第一吋长， 所述第 二预设条件为所述任意一轴的加速度持续大于第二阈值且持续吋间超 过第二吋长， 所述第三预设条件为所述加速度变化量持续小于第三阈 值且持续吋间超过第三吋长， 所述第四预设条件为所述静止事件发生 在自所述撞击事件发生后的第四吋长内， 其中， 所述第三吋长短于所 述第四吋长。
如权利要求 7所述的智能头盔， 其特征在于， 所述智能头盔进一步包 括警示灯， 所述警示灯用于幵启摔倒警示发光模式。
如权利要求 7所述的智能头盔， 其特征在于， 所述智能头盔进一步包 括 GPS定位模块和无线通信模块， 所述 GPS定位模块用于向所述控制 器发送当前的地理位置信息， 所述无线通信模块用于通过与所述智能 头盔相关联的移动终端向预设号码发送求救信息， 所述求救信息携带 所述当前地理位置信息。
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