WO2014035922A2 - Posture training device - Google Patents

Posture training device Download PDF

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Publication number
WO2014035922A2
WO2014035922A2 PCT/US2013/056718 US2013056718W WO2014035922A2 WO 2014035922 A2 WO2014035922 A2 WO 2014035922A2 US 2013056718 W US2013056718 W US 2013056718W WO 2014035922 A2 WO2014035922 A2 WO 2014035922A2
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WO
WIPO (PCT)
Prior art keywords
signal
microprocessor
posture
stimulus
measuring circuit
Prior art date
Application number
PCT/US2013/056718
Other languages
French (fr)
Other versions
WO2014035922A3 (en
Inventor
Jose A CUEVAS
Eduardo A CARBIA
Juan Ramon RABUÑAL-DOPICO
Alejandro Celestino PAZOS-SIERRA
Martin NOGUEIRA-SALGUEIRO
Original Assignee
Cuevas Jose A
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Publication date
Application filed by Cuevas Jose A filed Critical Cuevas Jose A
Priority to EP13833006.3A priority Critical patent/EP2928543A4/en
Publication of WO2014035922A2 publication Critical patent/WO2014035922A2/en
Publication of WO2014035922A3 publication Critical patent/WO2014035922A3/en

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Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813Specially adapted to be attached to a specific body part
    • A61B5/6823Trunk, e.g., chest, back, abdomen, hip
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/107Measuring physical dimensions, e.g. size of the entire body or parts thereof
    • A61B5/1071Measuring physical dimensions, e.g. size of the entire body or parts thereof measuring angles, e.g. using goniometers
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116Determining posture transitions
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/683Means for maintaining contact with the body
    • A61B5/6831Straps, bands or harnesses
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B23/00Exercising apparatus specially adapted for particular parts of the body
    • A63B23/02Exercising apparatus specially adapted for particular parts of the body for the abdomen, the spinal column or the torso muscles related to shoulders (e.g. chest muscles)
    • A63B23/0244Exercising apparatus specially adapted for particular parts of the body for the abdomen, the spinal column or the torso muscles related to shoulders (e.g. chest muscles) with signalling or indicating means, e.g. of incorrect posture, for deep-breathing exercises
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0062Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B24/00Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
    • A63B24/0087Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2560/00Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
    • A61B2560/02Operational features
    • A61B2560/0204Operational features of power management
    • A61B2560/0209Operational features of power management adapted for power saving
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/02Details of sensors specially adapted for in-vivo measurements
    • A61B2562/0219Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2562/00Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
    • A61B2562/06Arrangements of multiple sensors of different types
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235Details of waveform analysis
    • A61B5/7264Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/74Details of notification to user or communication with user or patient ; user input means
    • A61B5/7455Details of notification to user or communication with user or patient ; user input means characterised by tactile indication, e.g. vibration or electrical stimulation
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06Indicating or scoring devices for games or players, or for other sports activities
    • A63B71/0619Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
    • A63B2071/0655Tactile feedback
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B71/00Games or sports accessories not covered in groups A63B1/00 - A63B69/00
    • A63B71/06Indicating or scoring devices for games or players, or for other sports activities
    • A63B2071/0675Input for modifying training controls during workout
    • A63B2071/0683Input by handheld remote control
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/10Positions
    • A63B2220/13Relative positions
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/10Positions
    • A63B2220/16Angular positions
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/20Distances or displacements
    • A63B2220/24Angular displacement
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/40Acceleration
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/80Special sensors, transducers or devices therefor
    • A63B2220/83Special sensors, transducers or devices therefor characterised by the position of the sensor
    • A63B2220/836Sensors arranged on the body of the user
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2220/00Measuring of physical parameters relating to sporting activity
    • A63B2220/80Special sensors, transducers or devices therefor
    • A63B2220/89Field sensors, e.g. radar systems
    • AHUMAN NECESSITIES
    • A63SPORTS; GAMES; AMUSEMENTS
    • A63BAPPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
    • A63B2225/00Miscellaneous features of sport apparatus, devices or equipment
    • A63B2225/50Wireless data transmission, e.g. by radio transmitters or telemetry
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04MTELEPHONIC COMMUNICATION
    • H04M1/00Substation equipment, e.g. for use by subscribers
    • H04M1/72Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
    • H04M1/724User interfaces specially adapted for cordless or mobile telephones
    • H04M1/72403User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality

Definitions

  • the present disclosure relates generally to a noninvasive posture training device that continually monitors a user's spine, more particularly, a posture training device that measures the back's position and trains an individual to maintain movement patterns to ensure a particular posture.
  • Some well-known devices include devices capable of obtaining data which basically comprises means for receiving signals from sensors, means to store data related to sensors' signals, and means to communicate one device with other external devices .
  • the use of already existing devices for obtaining data in order to control posture is influenced by various factors .
  • the first factor is the use of only accelerometers for calculating the angles relative to the spinal column or backbone by ignoring the drift in the orientation over time, and thus progressively producing measurement errors from any tilting, bending, and straightness .
  • Another factor is the use of analogical sensors which results in mayor distortions in the captured signals .
  • Another factor is the size and energy consumption of a device, thus limiting working hours, increasing the device's surface, and hindering its ergonomics . Also another factor is the connection to other equipment through wired serial protocols with wires instead of wireless, thus allowing the user to move freely without being attached to anything. Similarly another factor is the lack of enough memory for data storage that allows subsequent analysis and an efficient use of the device for much more time. Furthermore another factor is the number of sections of the back to be analyzed for a correct study of all the possible postures by using 3 points to measure.
  • the present disclosure overcomes the disadvantages and shortcomings of prior art by disclosing a non- invasive device and a method for obtaining related data with one of more parameters that are detected through inertia measurement units, such as orientation sensors. Accordingly, it is an object of the present disclosure to provide a safe to use circuit with sensors for capturing the parameters related to the spine position, wherein said sensors are capable of sending digital signals to a computing platform device.
  • the computing platform device receives and uses a sequence of instructions to generate and store the data related to the spine position. Further, if needed, the data can be provided to the users at a different point from where the data is captured or measured for additional analysis.
  • the exemplary embodiment in accordance with the principles of the present disclosure comprises several low energy consume modules for data acquisition working in real time finding a more precise orientation in regard to the other tools for posture control.
  • the present modules and structure conceives greater precision in taking measurements and to real time capturing and analysis of tilting, bending, and straightness ; thus providing more independence and interdependence in the data transfer of each segment to be analyzed, and improving its versatility in choosing a particular function.
  • inertia measurement units such as accelerometers , gyroscopes, and magnetometers is incorporated to the sensor's circuit.
  • Still another object of the present disclosure is to provide the integration of a tri-axial accelerometer, a tri-axial gyroscope, and a tri-axial magnetometer per each segment to be analyzed.
  • Another object of this disclosure is to provide means to control the communication with the sensors and external devices .
  • the inertia measurement units are capable of receiving data are digital, thus avoiding any type of analogical/digital conversion.
  • a computing platform device comprising a microprocessor, wherein said microprocessor comprises a sequence of instructions to process in real time the data received from the inertia measurement units. Therefore, it is another object of this disclosure to provide means to control, analyze and generate alerts for incorrect positions .
  • the exemplary embodiment comprises a sensor holder, wherein said sensor holder fixes at least three different inertia measurement units to a particular back zone.
  • the sensor holder is configured to consider the ergonomics and form of the spine.
  • FIG.l shows a general structure connection for the measuring system in accordance with the principles of the present disclosure.
  • FIG.2 shows a general structure connection for the computing platform device in accordance with the principles of the present disclosure.
  • FIG.3 shows a general structure of the sensor holder first exemplary embodiment connected wireless external device in accordance with the principles of the present disclosure.
  • FIG.4 shows a flowchart exemplary embodiment of the back position training in accordance with the principles of the present disclosure.
  • FIG.5 shows a more detailed circuit for the measuring units in accordance with the principles of the present disclosure .
  • FIG.6 shows an exemplary embodiment of the computing platform device in accordance with the principles of the present disclosure.
  • FIG.7 shows an exemplary embodiment of the series of circuit for the measuring units connected to the computing platform device in accordance with the principles of the present disclosure.
  • FIG.8 shows a first exemplary embodiment of the noninvasive sensor holder in accordance with the principles of the present disclosure.
  • FIG.9A-9D show side and top views of the alert activation process for the first exemplary embodiment in accordance with the principles of the present disclosure .
  • FIG.10A-10B show back views of the alert activation process for the first exemplary embodiment in accordance with the principles of the present disclosure .
  • FIG.11A-11B shows more detailed views of the sensor holder for the first exemplary embodiment in accordance with the principles of the present disclosure .
  • FIG.12 shows a second exemplary embodiment of the noninvasive sensor holder in accordance with the principles of the present disclosure.
  • FIG.13A-13B show side views of the alert activation process for the second exemplary embodiment in accordance with the principles of the present disclosure .
  • FIG.14A-14B show back views of the alert activation process for the second exemplary embodiment in accordance with the principles of the present disclosure .
  • FIG.15A-15B show more detailed views of the sensor holder for the second exemplary embodiment in accordance with the principles of the present disclosure . DESCRIPTION OF THE PREFERRED EMBODIMENT
  • the system determines angles in real time in regard to each of the three (3) segments of the backbone in the X, Y, and Z components in order to calculate the tilting of each axis.
  • an approximation for calculating the tilting of each axis can be performed by directly integrating some accelerometers , but with the passing of cycles the orientation will drift and result in an orientation error and thus its correct calculation.
  • various inertia measurements units such as accelerometers, gyroscopes, and magnetometers (9 degrees of freedom) . This way one can efficiently avoid the possible drifts that happen over time, thus generating a very stable system.
  • the system will then require several sensors for each region of the back to be analyzed.
  • the general structure connection for the measuring system in accordance with the principles of the present disclosure comprises measuring units, wherein said measuring units comprises accelerometers, gyroscopes, and magnetometers.
  • the measuring units are in communication with the microprocessor through a switching unit or regulator. Further an energy source is coupled to the regulator for powering the measuring system. A more detailed structure is explained below.
  • FIG.2 shows a general structure connection for the computing platform device in accordance with the principles of the present disclosure.
  • the principal characteristics of the computing platform device are: the capacity to acquire effectively different types of digital signals, for example angles in X, Y, Z (tri-axial) for the accelerometer, gyroscope, and magnetometer) by integrating them in an algorithm in order to obtain the precise orientation of a rigid body; and the capacity to analyze the correct postures from the incorrect ones by generating an alert in the form of a vibrating or audible stimulus, by integrating an expert system capable of analyzing the new guidelines and generating an ideal response.
  • the computing device can be connected to a computer or other device (Smartphones , Tablets, etc..) through a USB port or even Bluetooth in order to share stored data.
  • a computer or other device Smartphones , Tablets, etc..
  • a USB port or even Bluetooth in order to share stored data.
  • the computing platform device system has a microcontroller, for example an AVR architecture microcontroller as nucleus.
  • the microcontroller may comprise an internal flash memory and EEPROM memory, internal as well, for data storage.
  • This microcontroller and the developed program that guides the system' s operation allows sharing store information through direct communication with a computer through the USB port as well as wireless communication through Bluetooth as shown in Fig. 3.
  • This communication uses a piece of hardware to translate data between parallel and serial form, for example a UART (Universal Asynchronous Receptor- Transmitter) standard.
  • the control of the feeding is done by a circuit in commutation that allows a 3.3 Vdc highly stable tension to exist out of a battery.
  • the communication among the posture training device PTD components is configured to be digital, thus reducing the interferences and the need for using an analogical- digital converter.
  • the data from each group of sensors is obtained independently through a processor per group.
  • the processor can follow the I2C protocol if desired.
  • each group comprises at least an accelerometer, a gyroscope and a magnetometer.
  • Each group of sensors is provided with a sequence of instructions. For example a sequence of instructions based on the direction cosine matrix (DCM) that continuously uses a 3x3 rotation matrix, defining the roll (r) , the pitch (p) , and the yaw (y) , which are the angles with respect to a fixed axis in reference to the Earth's directions.
  • DCM direction cosine matrix
  • DCM is a product matrix of other three individuals describing the rotation over axis "X", axis "Y, " and axis "Z.”
  • Gyroscopes measure the rotation over these axes in the backbone's framework.
  • Accelerometers measure the axes' acceleration over the plane, and the magnetometers measure the magnetization with respect to such axes.
  • the information obtained from the sensors will define 3 vectors, one for each sensor, being able to organize it in a matrix of sensors.
  • the DCM algorithm will consist of four stages:
  • the system will individually analyze the different regions of the backbone and the relations among them as a global system.
  • the system is divided into 3 specific zones (Lumbar Zone, Thoracic Zone, and Cervical Zone) , although able to add more to the system without modifying the hardware, only the number of sensor groups into which one would like to divide the backbone is available.
  • the placement of the sensors for this example has as an objective the analysis of the principal mobile curvatures of the back, thus placing each group of sensors in the following way: Cervical Cl-Tl; Thoracic Tl-Ll; Lumbar L1-L5.
  • Each group of sensors will be placed in a mobile curvature of the backbone, in order to obtain information in real time and transmit it to the corresponding microprocessor, which will perform a first filtering and organization of the obtained data, thus making it available to be sent to a main microprocessor.
  • This main microprocessor has been programmed to integrate the obtained data through the sensors in the previously described algorithm and to be able to obtain the Euler angles of each zone of the backbone to be analyzed, being able to correctly identify the group of sensors.
  • the rules described in the main microprocessor for the analysis of the obtained data will allow the user to adjust the parameters as necessary for each concrete situation, being able to vary the correct or incorrect deviation intervals, the time necessary for producing a stimulus, or even the stimulus time.
  • the integration of an expert system will allow automatic variations in those rules, thus achieving more efficiency in the system.
  • the backbone is showing deviations, making necessary their individual analysis or the analysis of existing interdependence among them.
  • the 3 curvatures of the backbone By controlling the 3 curvatures of the backbone, one can efficiently avoid bad postures and abnormalities such as lumbar lordosis and kyphosis . In the same way, muscular tension and pinching produced by an incorrect curvature of these 3 movable sections of the back that guide the correct behavior for the control of posture .
  • the posture control device aims to maintain the natural curve of the backbone in order to prevent muscular or biomechanical problems that cause pain or any other related pathology.
  • the learning device for the control of posture helps to facilitate therapeutic study and analysis, monitoring in real time the posture of the back and its 3 curvatures independently or relative to each other, thus producing a vibrating or audible stimulus when bad posture is detected in the patient. Consequently, the device users will be able to learn good posture habits that will benefit them for the rest of their lifetime.
  • the control of vibrating stimuli will be guided by some rules described by specialists in the field of back pain diagnoses, along with artificial intelligence systems, thus allowing improvements in the control of stimuli and a more specific and individual monitoring for each user and pathology.
  • the rules are converted into codes representing pre-determined values to be recognized by the posture training device, more particularly the computing platform device.
  • the pre-determined values are further compare with a current back position during the back posture analysis.
  • the non- invasive posture training device includes a clock in order to control data storage in an organized way and to analyze in a more coherent way the obtained results; since the learning device is wireless and will be able to be used during daily tasks, a micro SD memory has been included, thus allowing a greater quantity of data to be determined during a long period of time. This is why the device does not only work as a learning system, but it also works as a method for studying the adopted postures by following the parameters required by the specialist.
  • the parameters of the device will be able to be controlled through the main computing platform device by Observing the options to select in the display and thus configuring the different parameters as desired, for example pre-determined values.
  • Tri-axial accelerometer tri-axial gyroscope, and tri -axial magnetometer integration
  • the integration of the sensors to the users can be made in various ways, such as by sticking them to the indicated zone with adhesive pads, by integrating them to adjustable harnesses according to the anthropology of the individual, or by integrating them into t-shirts.
  • the computing platform device is desired to be integrated into a protective case, such as a box, for the protection of its components, and in reference to the global system, it may be adhered in various ways; whether by integrating in the harness or by pasting onto a belt.
  • An exemplary embodiment in accordance with the principle of the current invention is provided from Fig. 5 through Fig. 15.
  • the sequence of instructions that is used for the configuration of the learning device for the control of posture is the posture training system comprises different configuration options in order to work with different types of future versions, thus becoming a clear and simple interface for easy interpretation and handling by the specialists and the users.
  • Port speed the speed of the communications port is selected.
  • o Value- indicating window the acquired value of the selected zone is shown.
  • o System configuration comprises the selection of the desired parameters for the analysis, as time intervals for the stimulus or difference in degrees, individual selection of the segment or of the global system.
  • the non- invasive posture training device PTD structure as show in FIG. 5 through FIG. 15 for controlling of posture can be presented in two formats of reduced dimensions, one for measuring unit circuit sensors MC and the computing platform device Ml, wherein said computing platform device Ml comprises the main microprocessor.
  • the circuit sensor MC comprises at least an accelerometer A, at least a gyroscope G and a least a magnetometer M mounted on a circuit board B.
  • Fig. 6 is directed to the computing platform device Ml.
  • the computing platform device Ml comprises a Universal serial bus USB connection for sharing information and/or connecting to computers, as well as, for recharging the posture training device's batteries.
  • computing platform device Ml comprises a display D that guides one in the selection of parameters that one requires and in the response to the generated stimuli.
  • each circuit sensor MC is coupled wired or wireless to the computing platform device Ml.
  • the posture training device PTD as shown in Fig. 8 is ergonomic, safe to use and adjustable for each user 2.
  • the posture training device PTD comprises a center bar 1 and a belt 3 with attachable and adjustable means, such as conventional buckle and a snap latch, as in US. Patent 5,862526 here included by reference. Further, said center bar extends from said belt 3.
  • the center bar 1 comprises a top circuit sensor la configured to be located at the Cervical zone, a middle circuit sensor lb configured to be located at the thoracic zone and a bottom circuit sensor lc configured to be located at the lumbar zone.
  • the posture training device PTD detect a defected posture or a posture away from the set up parameter an alert AL is generated by the computing platform device 4 as disclosed above.
  • the defected motion is detected in at least three different dimensions per circuit sensor MC. For example a defected frontal posture, as shown in Fig 9B, a twisted torso posture, as shown in FIG. 9D, and/or a side defected posture as shown in Fig 10B.
  • the center bar 3 comprises a top section 100, a middle section 101 and a bottom section 102, as shown in Fig. 10A through Fig. 10B.
  • the inner part of the center bar 1 comprises recesses R in order to locate the circuit sensors la, lb, lc.
  • the top section 100 comprises at least several recesses R partially close, to each other, as shown in Fig 10B, providing different extensions of the top circuit la from the belt 3 depending on the selected recess R.
  • a second embodiment of the posture training device is shown from Fig. 11 through Fig. 15B.
  • the second embodiment similar from the first comprises the same elements but instead of three circuit sensors MC just use two.
  • control panel CP With the control panel CP, one can select using a input signal device, such as a keyboard, touch screen or any other means that translate information into a code accepted by the computing platform device 4 the desired parameters or pre-determined value, such as the specific control of a group of referenced sensors to a concrete segment of the backbone or the selection of a determined interval, or the specific time for any parameter to be analyzed.
  • a input signal device such as a keyboard, touch screen or any other means that translate information into a code accepted by the computing platform device 4 the desired parameters or pre-determined value, such as the specific control of a group of referenced sensors to a concrete segment of the backbone or the selection of a determined interval, or the specific time for any parameter to be analyzed.
  • the Led will appear turned on when the device is recharging its batteries, and as soon as it is turned off the batteries will be completely charged.
  • Good posture will be indicated as a correct position of the segments and the body in one moment and as a determined activity.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Surgery (AREA)
  • Public Health (AREA)
  • Biophysics (AREA)
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Abstract

A posture training device for monitoring posture is disclosed. The posture training device comprises at least a first measuring circuit unit attached to a first position on a user's body, and a second measuring circuit unit attached to a second position on the user's body. Each measuring circuit unit comprises an accelerometer, gyroscope, and magnetometers. Further the accelerometers, gyroscopes, and magnetometers generate a signal received by a computing platform unit. Any improper posture is indicated to the user by an alarm signal generated by the computing platform unit.

Description

TITLE OF THE DISCLOSURE
POSTURE TRAINING DEVICE
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT
N/A
RELATED APPLICATIONS
N/A
BACKGROUND OF THE DISCLOSURE
Field of the Disclosure
The present disclosure relates generally to a noninvasive posture training device that continually monitors a user's spine, more particularly, a posture training device that measures the back's position and trains an individual to maintain movement patterns to ensure a particular posture.
Discussion of the Background
Some well-known devices include devices capable of obtaining data which basically comprises means for receiving signals from sensors, means to store data related to sensors' signals, and means to communicate one device with other external devices .
The use of already existing devices for obtaining data in order to control posture is influenced by various factors . The first factor is the use of only accelerometers for calculating the angles relative to the spinal column or backbone by ignoring the drift in the orientation over time, and thus progressively producing measurement errors from any tilting, bending, and straightness . Another factor is the use of analogical sensors which results in mayor distortions in the captured signals .
Further, another factor is the size and energy consumption of a device, thus limiting working hours, increasing the device's surface, and hindering its ergonomics . Also another factor is the connection to other equipment through wired serial protocols with wires instead of wireless, thus allowing the user to move freely without being attached to anything. Similarly another factor is the lack of enough memory for data storage that allows subsequent analysis and an efficient use of the device for much more time. Furthermore another factor is the number of sections of the back to be analyzed for a correct study of all the possible postures by using 3 points to measure.
Yet another factor is the stimulus response that is done with strict parameters configured, without integrating any artificial intelligence system to recognize new correct or incorrect positions. Therefore, there is a need to provide an apparatus and method for back posture training that overcomes the disadvantages and shortcomings of the prior art . SUMMARY
In general, the present disclosure overcomes the disadvantages and shortcomings of prior art by disclosing a non- invasive device and a method for obtaining related data with one of more parameters that are detected through inertia measurement units, such as orientation sensors. Accordingly, it is an object of the present disclosure to provide a safe to use circuit with sensors for capturing the parameters related to the spine position, wherein said sensors are capable of sending digital signals to a computing platform device. The computing platform device receives and uses a sequence of instructions to generate and store the data related to the spine position. Further, if needed, the data can be provided to the users at a different point from where the data is captured or measured for additional analysis.
The exemplary embodiment in accordance with the principles of the present disclosure comprises several low energy consume modules for data acquisition working in real time finding a more precise orientation in regard to the other tools for posture control. The present modules and structure conceives greater precision in taking measurements and to real time capturing and analysis of tilting, bending, and straightness ; thus providing more independence and interdependence in the data transfer of each segment to be analyzed, and improving its versatility in choosing a particular function.
It is another object of the present disclosure to provide means to store data obtained by the inertia measurement units. In accordance with the principles of the present disclosure inertia measurement units such as accelerometers , gyroscopes, and magnetometers is incorporated to the sensor's circuit.
Still another object of the present disclosure is to provide the integration of a tri-axial accelerometer, a tri-axial gyroscope, and a tri-axial magnetometer per each segment to be analyzed.
Another object of this disclosure is to provide means to control the communication with the sensors and external devices . The inertia measurement units are capable of receiving data are digital, thus avoiding any type of analogical/digital conversion.
It is another object of this disclosure to provide means to store the information received by the computation platform device.
In accordance with the principles of the present disclosure comprises a computing platform device comprising a microprocessor, wherein said microprocessor comprises a sequence of instructions to process in real time the data received from the inertia measurement units. Therefore, it is another object of this disclosure to provide means to control, analyze and generate alerts for incorrect positions .
Further in accordance with the principles of the present disclosure the exemplary embodiment comprises a sensor holder, wherein said sensor holder fixes at least three different inertia measurement units to a particular back zone. The sensor holder is configured to consider the ergonomics and form of the spine.
The disclosure itself, both as to its configuration and its mode of operation will be best understood, and additional objects and advantages thereof will become apparent, by the following detailed description of a preferred embodiment taken in conjunction with the accompanying drawings .
The Applicant hereby asserts, that the disclosure of the present application may include more than one invention, and, in the event that there is more than one invention, that these inventions may be patentable and non- obvious one with respect to the other.
Further, the purpose of the accompanying abstract is to enable the U.S. Patent and Trademark Office and the public generally, and especially the scientists, engineers, and practitioners in the art who are not familiar with patent or legal terms or phraseology, to determine quickly from a cursory inspection the nature and essence of the technical disclosure of the application. The abstract is neither intended to define the disclosure of the application, which is measured by the claims, nor is it intended to be limiting as to the scope of the disclosure in any way.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are incorporated herein, constitute part of the specification and illustrate the preferred embodiment of the disclosure.
FIG.l shows a general structure connection for the measuring system in accordance with the principles of the present disclosure.
FIG.2 shows a general structure connection for the computing platform device in accordance with the principles of the present disclosure.
FIG.3 shows a general structure of the sensor holder first exemplary embodiment connected wireless external device in accordance with the principles of the present disclosure.
FIG.4 shows a flowchart exemplary embodiment of the back position training in accordance with the principles of the present disclosure.
FIG.5 shows a more detailed circuit for the measuring units in accordance with the principles of the present disclosure .
FIG.6 shows an exemplary embodiment of the computing platform device in accordance with the principles of the present disclosure.
FIG.7 shows an exemplary embodiment of the series of circuit for the measuring units connected to the computing platform device in accordance with the principles of the present disclosure.
FIG.8 shows a first exemplary embodiment of the noninvasive sensor holder in accordance with the principles of the present disclosure.
FIG.9A-9D. show side and top views of the alert activation process for the first exemplary embodiment in accordance with the principles of the present disclosure .
FIG.10A-10B show back views of the alert activation process for the first exemplary embodiment in accordance with the principles of the present disclosure .
FIG.11A-11B. shows more detailed views of the sensor holder for the first exemplary embodiment in accordance with the principles of the present disclosure .
FIG.12 shows a second exemplary embodiment of the noninvasive sensor holder in accordance with the principles of the present disclosure.
FIG.13A-13B. show side views of the alert activation process for the second exemplary embodiment in accordance with the principles of the present disclosure .
FIG.14A-14B show back views of the alert activation process for the second exemplary embodiment in accordance with the principles of the present disclosure .
FIG.15A-15B show more detailed views of the sensor holder for the second exemplary embodiment in accordance with the principles of the present disclosure . DESCRIPTION OF THE PREFERRED EMBODIMENT
The system determines angles in real time in regard to each of the three (3) segments of the backbone in the X, Y, and Z components in order to calculate the tilting of each axis. However, an approximation for calculating the tilting of each axis can be performed by directly integrating some accelerometers , but with the passing of cycles the orientation will drift and result in an orientation error and thus its correct calculation. In order to avoid this situation and obtain a precise orientation over time, it is necessary to integrate through an algorithm various inertia measurements units, such as accelerometers, gyroscopes, and magnetometers (9 degrees of freedom) . This way one can efficiently avoid the possible drifts that happen over time, thus generating a very stable system. The system will then require several sensors for each region of the back to be analyzed.
Referring to FIG. 1, the general structure connection for the measuring system in accordance with the principles of the present disclosure comprises measuring units, wherein said measuring units comprises accelerometers, gyroscopes, and magnetometers. The measuring units are in communication with the microprocessor through a switching unit or regulator. Further an energy source is coupled to the regulator for powering the measuring system. A more detailed structure is explained below.
FIG.2 shows a general structure connection for the computing platform device in accordance with the principles of the present disclosure. The principal characteristics of the computing platform device are: the capacity to acquire effectively different types of digital signals, for example angles in X, Y, Z (tri-axial) for the accelerometer, gyroscope, and magnetometer) by integrating them in an algorithm in order to obtain the precise orientation of a rigid body; and the capacity to analyze the correct postures from the incorrect ones by generating an alert in the form of a vibrating or audible stimulus, by integrating an expert system capable of analyzing the new guidelines and generating an ideal response.
Further the computing device can be connected to a computer or other device (Smartphones , Tablets, etc..) through a USB port or even Bluetooth in order to share stored data. In addition to its adjusted intake in performance, that allows the design and creation of a system for the determination of complex data with a simple system of energy input .
The computing platform device system has a microcontroller, for example an AVR architecture microcontroller as nucleus. The microcontroller may comprise an internal flash memory and EEPROM memory, internal as well, for data storage. This microcontroller and the developed program that guides the system' s operation allows sharing store information through direct communication with a computer through the USB port as well as wireless communication through Bluetooth as shown in Fig. 3. This communication uses a piece of hardware to translate data between parallel and serial form, for example a UART (Universal Asynchronous Receptor- Transmitter) standard. The control of the feeding is done by a circuit in commutation that allows a 3.3 Vdc highly stable tension to exist out of a battery.
The communication among the posture training device PTD components is configured to be digital, thus reducing the interferences and the need for using an analogical- digital converter. In addition, the data from each group of sensors is obtained independently through a processor per group. The processor can follow the I2C protocol if desired.
Brief description of the steps to follow with the method of using the current disclosure :
As shown in Fig 4, each group comprises at least an accelerometer, a gyroscope and a magnetometer. Each group of sensors is provided with a sequence of instructions. For example a sequence of instructions based on the direction cosine matrix (DCM) that continuously uses a 3x3 rotation matrix, defining the roll (r) , the pitch (p) , and the yaw (y) , which are the angles with respect to a fixed axis in reference to the Earth's directions.
DCM is a product matrix of other three individuals describing the rotation over axis "X", axis "Y, " and axis "Z." Gyroscopes measure the rotation over these axes in the backbone's framework. Accelerometers measure the axes' acceleration over the plane, and the magnetometers measure the magnetization with respect to such axes.
The information obtained from the sensors will define 3 vectors, one for each sensor, being able to organize it in a matrix of sensors. The DCM algorithm will consist of four stages:
a . Matrix update :
Means a multiplication matrix of DCM with the integration matrix of gyres.
b. Normalization.
c . Correction of deviations .
d. Euler angles.
This way one will determine the Euler angles in each axis within the backbone's framework.
Process of the performance example:
The system will individually analyze the different regions of the backbone and the relations among them as a global system. In the selected example, the system is divided into 3 specific zones (Lumbar Zone, Thoracic Zone, and Cervical Zone) , although able to add more to the system without modifying the hardware, only the number of sensor groups into which one would like to divide the backbone is available. The placement of the sensors for this example has as an objective the analysis of the principal mobile curvatures of the back, thus placing each group of sensors in the following way: Cervical Cl-Tl; Thoracic Tl-Ll; Lumbar L1-L5.
Each group of sensors will be placed in a mobile curvature of the backbone, in order to obtain information in real time and transmit it to the corresponding microprocessor, which will perform a first filtering and organization of the obtained data, thus making it available to be sent to a main microprocessor. This main microprocessor has been programmed to integrate the obtained data through the sensors in the previously described algorithm and to be able to obtain the Euler angles of each zone of the backbone to be analyzed, being able to correctly identify the group of sensors.
The rules described in the main microprocessor for the analysis of the obtained data will allow the user to adjust the parameters as necessary for each concrete situation, being able to vary the correct or incorrect deviation intervals, the time necessary for producing a stimulus, or even the stimulus time. In addition, the integration of an expert system will allow automatic variations in those rules, thus achieving more efficiency in the system.
If any of the curvatures is great or flat, then the backbone is showing deviations, making necessary their individual analysis or the analysis of existing interdependence among them. By controlling the 3 curvatures of the backbone, one can efficiently avoid bad postures and abnormalities such as lumbar lordosis and kyphosis . In the same way, muscular tension and pinching produced by an incorrect curvature of these 3 movable sections of the back that guide the correct behavior for the control of posture .
The posture control device aims to maintain the natural curve of the backbone in order to prevent muscular or biomechanical problems that cause pain or any other related pathology. The learning device for the control of posture helps to facilitate therapeutic study and analysis, monitoring in real time the posture of the back and its 3 curvatures independently or relative to each other, thus producing a vibrating or audible stimulus when bad posture is detected in the patient. Consequently, the device users will be able to learn good posture habits that will benefit them for the rest of their lifetime.
The control of vibrating stimuli will be guided by some rules described by specialists in the field of back pain diagnoses, along with artificial intelligence systems, thus allowing improvements in the control of stimuli and a more specific and individual monitoring for each user and pathology. The rules are converted into codes representing pre-determined values to be recognized by the posture training device, more particularly the computing platform device. The pre-determined values are further compare with a current back position during the back posture analysis.
The non- invasive posture training device includes a clock in order to control data storage in an organized way and to analyze in a more coherent way the obtained results; since the learning device is wireless and will be able to be used during daily tasks, a micro SD memory has been included, thus allowing a greater quantity of data to be determined during a long period of time. This is why the device does not only work as a learning system, but it also works as a method for studying the adopted postures by following the parameters required by the specialist.
The parameters of the device will be able to be controlled through the main computing platform device by Observing the options to select in the display and thus configuring the different parameters as desired, for example pre-determined values.
The most important characteristics of the circuits are the following:
• Group of sensors :
o Digital communication following I2C protocol, o Microcontroller incorporation,
o Low-consumption required feeding,
o Design minimization.
o Tri-axial accelerometer, tri-axial gyroscope, and tri -axial magnetometer integration,
o Integrated circuits for each tri-axial accelerometer, tri-axial gyroscope, and tri-axial magnetometer .
• programmed main microcontroller:
o Internal memory storing the sequence of instructions .
o Capability to store the device configurations, o Fast transmission of data.
The integration of the sensors to the users can be made in various ways, such as by sticking them to the indicated zone with adhesive pads, by integrating them to adjustable harnesses according to the anthropology of the individual, or by integrating them into t-shirts. Below is the discussion of a preferred embodiment. The computing platform device is desired to be integrated into a protective case, such as a box, for the protection of its components, and in reference to the global system, it may be adhered in various ways; whether by integrating in the harness or by pasting onto a belt. An exemplary embodiment in accordance with the principle of the current invention is provided from Fig. 5 through Fig. 15.
The sequence of instructions that is used for the configuration of the learning device for the control of posture is the posture training system comprises different configuration options in order to work with different types of future versions, thus becoming a clear and simple interface for easy interpretation and handling by the specialists and the users.
The principal configuration options are the following: o Port speed: the speed of the communications port is selected.
o Value- indicating window: the acquired value of the selected zone is shown. o System configuration: comprises the selection of the desired parameters for the analysis, as time intervals for the stimulus or difference in degrees, individual selection of the segment or of the global system.
o Software control panels: where one can initiate the communication, stop it, store the data obtained by the system, Bluetooth connection, and exit.
o Real-time visualization window of the backbone ' s behavior .
o Diagnostics window.
o Indicating window for the incorrect postures adopted during the analysis.
The non- invasive posture training device PTD structure, as show in FIG. 5 through FIG. 15 for controlling of posture can be presented in two formats of reduced dimensions, one for measuring unit circuit sensors MC and the computing platform device Ml, wherein said computing platform device Ml comprises the main microprocessor.
In Fig. 5 the circuit sensor MC comprises at least an accelerometer A, at least a gyroscope G and a least a magnetometer M mounted on a circuit board B. Fig. 6 is directed to the computing platform device Ml. The computing platform device Ml comprises a Universal serial bus USB connection for sharing information and/or connecting to computers, as well as, for recharging the posture training device's batteries. In addition, computing platform device Ml comprises a display D that guides one in the selection of parameters that one requires and in the response to the generated stimuli. In reference to the collection of sensors, as shown in Fig. 6, each circuit sensor MC is coupled wired or wireless to the computing platform device Ml.
Each circuit sensor MC and said computing platform device Ml are coupled to a posture training device PTD. The posture training device PTD, as shown in Fig. 8 is ergonomic, safe to use and adjustable for each user 2. The posture training device PTD comprises a center bar 1 and a belt 3 with attachable and adjustable means, such as conventional buckle and a snap latch, as in US. Patent 5,862526 here included by reference. Further, said center bar extends from said belt 3.
The center bar 1 comprises a top circuit sensor la configured to be located at the Cervical zone, a middle circuit sensor lb configured to be located at the thoracic zone and a bottom circuit sensor lc configured to be located at the lumbar zone. Wherein the posture training device PTD detect a defected posture or a posture away from the set up parameter an alert AL is generated by the computing platform device 4 as disclosed above. The defected motion is detected in at least three different dimensions per circuit sensor MC. For example a defected frontal posture, as shown in Fig 9B, a twisted torso posture, as shown in FIG. 9D, and/or a side defected posture as shown in Fig 10B.
The center bar 3 comprises a top section 100, a middle section 101 and a bottom section 102, as shown in Fig. 10A through Fig. 10B. The inner part of the center bar 1 comprises recesses R in order to locate the circuit sensors la, lb, lc. The top section 100 comprises at least several recesses R partially close, to each other, as shown in Fig 10B, providing different extensions of the top circuit la from the belt 3 depending on the selected recess R.
A second embodiment of the posture training device is shown from Fig. 11 through Fig. 15B. The second embodiment similar from the first comprises the same elements but instead of three circuit sensors MC just use two.
With the control panel CP, one can select using a input signal device, such as a keyboard, touch screen or any other means that translate information into a code accepted by the computing platform device 4 the desired parameters or pre-determined value, such as the specific control of a group of referenced sensors to a concrete segment of the backbone or the selection of a determined interval, or the specific time for any parameter to be analyzed.
The Led will appear turned on when the device is recharging its batteries, and as soon as it is turned off the batteries will be completely charged.
Good posture will be indicated as a correct position of the segments and the body in one moment and as a determined activity.
The disclosure is not limited to the precise configuration described above. While the disclosure has been described as having a preferred design, it is understood that many changes, modifications, variations and other uses and applications of the subject disclosure will, however, become apparent to those skilled in the art without materially departing from the novel teachings and advantages of this disclosure after considering this specification together with the accompanying drawings. Accordingly, all such changes, modifications, variations and other uses and applications which do not depart from the spirit and scope of the disclosure are deemed to be covered by this disclosure as defined in the following claims and their legal equivalents. In the claims, means-plus-function clauses, if any, are intended to cover the structures described herein as performing the recited function and not only structural equivalents but also equivalent structures .
All of the patents, patent applications, and publications recited herein, and in the Declaration attached hereto, if any, are hereby incorporated by reference as if set forth in their entirety herein. All, or substantially all, the components disclosed in such patents may be used in the embodiments of the present disclosure, as well as equivalents thereof. The details in the patents, patent applications, and publications incorporated by reference herein may be considered to be incorporable at applicant's option, into the claims during prosecution as further limitations in the claims to patently distinguish any amended claims from any applied prior art .

Claims

Claims
1. An apparatus, comprising: a plurality of measuring circuit units comprising at least a first measuring circuit and a second measuring circuit; a computing platform; an adjustable posture training device; wherein each measuring circuit comprises a circuit board with tri-axial measurement sensors; and wherein said posture device comprises at least a belt and a central bar, wherein said central bar is configured to be positioned on a user's back and receives said first measuring circuit at the lumbar area and said second measuring circuit at thoracic area.
2. The apparatus of claim 1, wherein each measuring unit comprises accelerometer generating a first signal, gyroscope generating a second signal, and magnetometer generating a third signal.
3. The apparatus of claim 2, wherein each measuring unit comprises a first microprocessor receiving the first signal, second signal, and third signal.
4. The apparatus of claim 1 or 3, wherein said computing platform comprises a second microprocessor receiving a first microprocessor signal.
5. The apparatus of claim 3, wherein said computing platform comprises ; a data base to store at least the first signal, second signal, and third signal; a clock to control the information stored in the database; means for sharing information with external device; means for comparing a first microprocessor's signal with a pre-determined value; and means to generate a stimulus .
6. The apparatus of claim 5, wherein said stimulus is selected from a group of audible stimulus or vibration.
7. The apparatus of claim 5, wherein said means for comparing the first microprocessor's signal comprises a second microprocessor .
8. The apparatus of claim 5, wherein said means for sharing information with external device comprises means for direct communication.
9. The apparatus of claim 5, wherein said means for sharing information with external device comprises means for wireless communication.
10. Learning device for the control of the posture comprising : inertia measurement units for determining angles and orientations ; means for storing data from the inertia measurement units; at least one microcontroller; and a posture device for receiving the inertia measurement units, wherein said posture device holds the inertia measurement units at a particular position of a spine; and wherein each inertia measurement unit comprises an accelerometer, an gyroscope, and a magnetometer.
11. The learning device of claim 10, wherein each inertia measuring unit comprises a first microprocessor receiving a first signal, a second signal and third signal generated from the accelerometer, the gyroscope, and the magnetometer .
12. The learning device of claim 11, wherein said microcontroller comprises a second microprocessor receiving a first microprocessor's signal.
13. The learning device of claim 10, wherein said microcontroller comprises; a data base to store at least the first signal and second signal ; a clock to control the information stored in the database; means for sharing information with an external device; means for comparing a first microprocessor's signal with a pre-determined value; and means to generate a stimulus .
14. The learning device of claim 13, wherein said stimulus is selected from a group of audible stimulus or vibration.
15. The learning device of claim 13, wherein said means for comparing the first microprocessor's signal comprises a second microprocessor.
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GB2540335A (en) * 2015-05-12 2017-01-18 Thomson Siobhan Position correction device
US9763603B2 (en) 2014-10-21 2017-09-19 Kenneth Lawrence Rosenblood Posture improvement device, system, and method
GB2560909A (en) * 2017-03-27 2018-10-03 270 Vision Ltd Movement sensor
GB2579684A (en) * 2017-10-03 2020-07-01 Virtualclinic Direct Ltd Data capture device

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US7431703B2 (en) * 2003-03-15 2008-10-07 Salvi Frank J Apparatus and method for measuring and monitoring range of motion of the lumbar spine
FR2868281B1 (en) * 2004-03-30 2023-06-23 Commissariat Energie Atomique METHOD FOR DETERMINING THE MOVEMENTS OF A PERSON.
US8366641B2 (en) * 2005-11-18 2013-02-05 Cardiac Pacemakers, Inc. Posture detector calibration and use
US8688225B2 (en) * 2008-07-11 2014-04-01 Medtronic, Inc. Posture state detection using selectable system control parameters
US8217797B2 (en) * 2009-09-15 2012-07-10 Dikran Ikoyan Posture training device

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Publication number Priority date Publication date Assignee Title
US9763603B2 (en) 2014-10-21 2017-09-19 Kenneth Lawrence Rosenblood Posture improvement device, system, and method
GB2540335A (en) * 2015-05-12 2017-01-18 Thomson Siobhan Position correction device
GB2540335B (en) * 2015-05-12 2019-11-13 Thomson Siobhan Position correction device
GB2560909A (en) * 2017-03-27 2018-10-03 270 Vision Ltd Movement sensor
WO2018178623A1 (en) * 2017-03-27 2018-10-04 270 Vision Ltd Movement sensor
GB2560909B (en) * 2017-03-27 2020-12-02 270 Vision Ltd Movement sensor
GB2579684A (en) * 2017-10-03 2020-07-01 Virtualclinic Direct Ltd Data capture device

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