JP2011505015A - System, method and computer program product for measuring pressure points - Google Patents

Abstract

  Force sensing methods, systems, and computer program products may be used to sense pressure at multiple points on a user's foot, including bones, joints, muscles, tendons, and ligaments. Such systems, methods, and computer program products sense pressure along the bottom of the user's foot during sports training and in monitoring applications, computer games, and diagnostic systems. In particular, the system generally includes a transducer having a plurality of target points, an insole node for collecting and transmitting data sensed at the plurality of target points, and a first for coupling the data to the network. And a second means for coupling the same data to the collector node and then to the computer.

Description

Copyright Warning Part of the description of this patent document may also include matters under copyright protection. The copyright owner has no objection to the reproduction of any patent document or patent information disclosure as long as it appears in a file or record document of the United States Patent and Trademark Office; otherwise, all copyrights are reserved. To do.

This application claims the benefit of the following related applications: US patent application Ser. No. 12 / 155,558, filed Jun. 5, 2008. This application likewise takes advantage of US Provisional Patent Application No. 60 / 924,931, filed June 5, 2007, and US Provisional Patent Application No. 60 / 996,608, filed November 27, 2007. Each of which is incorporated herein by reference in its entirety.

  The present invention, in its illustrative embodiments, relates generally to systems, methods, and computer program products for pressure sensing, and more particularly, sports training and monitoring applications, computer games, as will become apparent below. And a system, method, and computer program product for sensing pressure along the bottom of a user's foot during use of a diagnostic system. However, it will be readily appreciated by those skilled in the art that the following embodiments can be applied to other pressure sensing applications.

  Athletes use a variety of metrics to measure their performance and record workouts. Record metrics and analyze them during and after the workout. For example, an interval workout generally involves intense or intense activity, somewhat intense or moderate intensity activity, and multiple sets of rest. This intense activity may be represented by a range of metrics that correlate to the desired intensity or strength for a particular athlete. Similarly, periods of rest or somewhat intense activity may be expressed as a range or metric that correlates to a desired calm state for a particular athlete.

  Thus, a system that senses pressure along the bottom of the user's foot to record and analyze such metrics during use of sports training and monitoring applications, computer games, and diagnostic systems, It would be desirable to provide methods and computer program products.

  The human foot is mechanically complex and has strong structural strength. The ankle functions as a base, a shock absorber (buffer part), and a propulsion engine. The foot can withstand intense pressure (ie, a range of about a few tons while running a mile (one mile is about 1609m)) and can provide flexibility and elasticity.

  The feet and ankles consist of 26 bones (ie, nearly 1/4 of the human bone is in the foot); 33 joints; more than 100 muscles, tendons (ie, fibrous tissue that connects muscles to bone) ), And ligaments (ie, fibrous tissue connecting bones to other bones); and vascular tissue networks, nerves, skin, and soft tissues.

  These components work together to support the body, maintain body balance, and provide mobility to the body. Any structural defect or dysfunction in any part can cause problems anywhere in the body. Abnormalities in other parts of the body can cause problems with the feet. Embodiments of the present invention help to mitigate such problems by assisting in sensing pressure applied to multiple points on the user's foot.

  Structurally, the foot has three main parts: a forefoot, a midfoot, and a hindfoot. 2A and 2B, the forefoot part, that is, the front part of the foot, is composed of five toes (referred to as ribs or phalanges) and a long bone (metatarsal bone) connecting them. Each toe (rib or phalange) is composed of several small bones. The big toe (also known as thumb or first heel) has two ribs, a distal bone and a proximal bone. The big toe has one joint called the interphalangeal joint. The big toe forms a joint with the first metatarsal head and is called the first metatarsophalangeal joint (abbreviated as MTPJ). Below the first metatarsal head are two small round bones called seed bones. The other four toes each have three bones and two joints. The ribs are connected to the metatarsal bone by five metatarsophalangeal joints in the thumb ball. The forefoot supports half of the weight and balances the pressure on the ball.

  The midfoot or midfoot has five irregularly shaped tarsal bones, forms an arch or plantar arch, and serves as a shock absorber. The midfoot bones are connected to the forefoot and hindfoot by muscles and plantar fascia (arch ligament).

  The rear foot portion, that is, the rear portion of the foot is composed of three joints, and the middle foot portion is connected to the ankle (talar bone). The upper part of the talus is connected to the two long bones (tibia and fibula) of the lower limb to form a hinge, thereby allowing the foot to move up and down. The heel bone (rib) is the largest bone in the foot. The radius joins the talus to form the subtalar joint. The bottom of the rib is softened by a fat layer.

  Muscle, tendon, and ligament networks support the bones and joints of the foot. There are 20 muscles in the foot, and the foot is given its shape by holding the bone in an appropriate location, and stretches and contracts to give movement. The main muscles of the foot are: the anterior tibial muscle that allows the foot to move upwards; the posterior tibial muscle that supports the arch; the tibial peroneal muscle that controls the movement of the ankle outside; Extensors that help initiate the action to go to; and flexors that help stabilize the toes against the ground. Smaller muscles allow the toes to be lifted and bent.

  In the foot, there is an elastic tissue (tendon) that connects muscles to bones and joints. The largest and strongest tendon of the foot is the Achilles tendon, which extends from the calf muscle to the heel. Its strength and joint function make it easy to run, jump, climb stairs, and stretch your body on your toes. The ligament holds the tendon in place and stabilizes the joint. Among these, the longest plantar fascia forms an arch from the heel to the toes on the sole of the foot. As the plantar fascia contracts, the arch is curved and flattened to provide balance and give the foot the strength to start walking. The medial ligaments on the outside and lateral ligaments of the foot provide stability and allow the foot to be raised or lowered. The skin, blood vessels, and nerves give the foot its shape and durability, provide cell regeneration and the necessary nutrients for the muscle, and control its various movements.

  The method, system, and computer program product for pressure sensing can be used to sense pressure at multiple points, including bones, joints, muscles, tendons, and ligaments, particularly of a user's foot. .

  These and other objects, advantages, and novel features according to embodiments of the present invention generally include a transducer having a plurality of target points and collecting data sensed at the plurality of target points and Achieved by a sensing system comprising: a first means for transmitting, the first means for coupling the data to the network; and the second means for coupling the same data to the collector node and then to the analyzing computer. The

  “Computer” means one or more devices and / or one or more devices that can receive structured input, process the structured input and produce processing results as output according to defined rules. Let's say the system. Examples of computers are: computers; stationary and / or portable computers; single processors, multiprocessors, or computers with multicore processors that can operate in parallel and / or non-parallel; general purpose computers; supercomputers; mainframes; Small computers; Small computers; Workstations; Microcomputers; Servers; Clients; Interactive televisions; Web appliances; Communication devices that can connect to the Internet; Hybrid computers with computers and interactive televisions; Portable computers; Tablet personal computers (PCs); Terminal (PDA); mobile phone; specific application to emulate computer and / or software Hardware, eg, digital signal processor (DSP), field programmable gate array (FPGA), application specific integrated circuit (ASIC), application specific instruction set processor (ASIP), one chip, multiple chips, on chip Data collection device; optical computer; quantum computer; biocomputer; and receive data, process data according to one or more stored software programs, generate results, and typically an input device And an apparatus that may include an output device, a storage device, an arithmetic device, a logical arithmetic device, and a control device.

  “Software” refers to a prescribed rule for operating a computer. Examples of software include: code segments in one or more computer readable languages; graphical and / or textual instructions; applets; precompiled code; translated code; compiled code; and computer programs Can do.

  “Computer-readable medium” refers to any storage device used to store computer-accessible data. Examples of computer readable media are: magnetic hard disk; floppy disk; optical disk, such as CD-ROM and DVD; magnetic tape; flash memory; memory chip; and / or other types of machine readable instructions A medium can be mentioned.

  “Computer system” refers to a system having one or more computers, each computer including a computer-readable medium embodying software for operating the computer or one or more of its components. . Examples of computer systems include: a distributed computer system for processing information by a computer system connected to a network; two or more connected via a network to send and / or receive information between computer systems A computer system; a computer system including two or more processors in a single computer; and receiving data, processing data according to one or more stored software programs, generating results thereof; and One or more devices and / or one or more systems that may typically include an input device, an output device, a storage device, a computing device, a logic computing device, and a control device may be mentioned.

  “Network” refers to a plurality of computers and associated devices that may be connected by a communication device. The network can include permanent connections such as cables, or temporary connections such as those made by telephones or other communication lines. The network can further include wired connections (eg, coaxial cables, twisted pairs, optical fibers, waveguides, etc.) and / or wireless connections (eg, radio frequency waves, free space optical waves, acoustic waves, etc.). Examples of networks include: the Internet, eg, the Internet; an intranet; a local area network (LAN); a wide area network (WAN); and a combination of networks, such as the Internet and an intranet. Exemplary networks may be any of a number of protocols, such as Internet Protocol (IP), Asynchronous Transfer Mode (ATM), and / or Synchronous Optical Network (SONET), User Datagram Protocol (UDP), IEEE 802. It can operate with x and the like.

  Embodiments of the invention can include an apparatus for performing the operations described herein. The apparatus may be specially configured for the desired purpose, or it may include a general purpose device that is selectively activated or reconfigured by a program stored on the device.

  Embodiments of the invention may also be implemented in any one of hardware, firmware, and software, or a combination of hardware, firmware, and software. They may be executed as instructions stored on a machine-readable medium. These machine readable media may be read and executed by a computing platform to perform the operations described herein.

  In the following description and claims, the terms “computer program medium” and “computer readable medium” are generally used to refer to media such as a removable storage drive, a hard disk attached to a hard disk drive, etc. , But not limited to this. These computer program products may provide software to the computer system. Embodiments of the invention relate to such computer program products.

  “One embodiment”, “embodiment”, “exemplary embodiment”, “various embodiments” and the like are intended to include specific features, structures or characteristics in the description of embodiments of the invention, Not all embodiments necessarily include specific features, structures or characteristics. Furthermore, repeated use of the terms “in one embodiment” or “in an exemplary embodiment” does not necessarily refer to the same embodiment, but may.

  In the following description and claims, the terms “coupled” and “connected” may be used with their derivatives. It should be understood that these terms are not synonymous with each other. On the contrary, in certain embodiments, “connected” is used to indicate that two or more elements are in direct physical or electrical contact with each other. “Coupled” means that two or more elements are in direct physical or electrical contact. However, “coupled” also means that two or more elements are not in direct contact with each other but are still cooperatively interacting.

  Overall, the algorithm is considered to be a self-consistent sequence of actions or operations that produce the desired result. These include physical treatment of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, etc., primarily because they are commonly available. However, it should be understood that all of these and similar terms relate to the appropriate physical quantities and that only convenient labels are applied to these quantities.

  Unless otherwise stated, and as will be apparent from the following description and claims, terms such as “processing”, “computing”, “calculation”, “decision”, etc. were used throughout this specification. The description manipulates data represented as physical, e.g., electronic quantities in the computer system registers and / or memory and / or stores, transmits, computer system memory, registers or other such information. It should be understood that it refers to the operation and / or processing of a computer or computing system, or similar electronic computing device, that translates into other data that is also displayed in the same manner as a physical quantity in a display device.

  Similarly, the term “processor” refers to any device or device that can process electronic data from a register and / or memory, convert the electronic data to other electronic data, and store it in the register and / or memory. Pointing to the department. A “computational platform” can include one or more processors.

  The above and other features of the present invention will become apparent from the following description of exemplary embodiments, and like reference numerals are generally identical, functionally similar, and / or structural, as illustrated in the accompanying drawings. Shows similar elements. Usually, the leftmost digit of the corresponding reference number indicates the figure in which the element first appears.

1 shows a sensing system according to a first embodiment of the present invention. 2A and 2B show a portion of a person's foot, a portion of which is sensed by the sensing system shown in FIG. FIG. 2 shows a portion of the sensing system shown in FIG. Figure 4 shows a schematic format of an electrode grid selector mapping means that can be used with the converter shown in Figure 3; Fig. 5 shows in schematic format a controller incorporating the electrode grid selector mapping means shown in Fig. 4; Figure 6 shows a graph showing the dependence of the transducer on resistance as a function of the pressure sensed by the transducer. FIG. 7 shows a transmission flow diagram of data sensed by the sensing system of FIGS. 1 and 3-6. Fig. 5 shows a first electrode grid layer of a converter according to another embodiment of the invention. Fig. 4 shows a second electrode grid layer that can be used with a first electrode grid layer of a converter according to another embodiment of the invention. 10 shows a portion of a schematic format of an RF module that can be used with the first and second electrode grid layers shown in FIGS. 10 shows a portion of a schematic format of an RF module that can be used with the first and second electrode grid layers shown in FIGS. 10 shows a portion of a schematic format of an RF module that can be used with the first and second electrode grid layers shown in FIGS. 10 shows a portion of a schematic format of an RF module that can be used with the first and second electrode grid layers shown in FIGS. 10 shows a portion of a schematic format of an RF module that can be used with the first and second electrode grid layers shown in FIGS. 10 shows a portion of a schematic format of an RF module that can be used with the first and second electrode grid layers shown in FIGS. FIG. 10 shows first and second algorithms that may be used with the converter according to FIGS. 8, 9 and 10A-10F. FIG. 10 shows first and second algorithms that may be used with the converter according to FIGS. 8, 9 and 10A-10F.

  Hereinafter, exemplary embodiments will be described in detail. Although specific exemplary embodiments are described, it should be understood that this is for illustrative purposes only. In describing and illustrating the exemplary embodiments, certain terminology is used for the sake of clarity. However, the present invention is in no way limited to the specific term examples so selected. Those skilled in the art will appreciate that other components and configurations may be used without departing from the spirit and scope of the present invention. It is to be understood that each specific element includes all technical equivalents that operate in a similar manner to accomplish a similar purpose. Thus, the examples and embodiments described herein are non-limiting examples.

  Referring now to the drawings, like reference numerals and characters indicate like or corresponding parts and steps throughout each of the many views. FIG. 1 shows a sensing system 100 according to a first embodiment of the present invention. The system 100 generally includes a transducer 102 having a plurality of target points 104a, 104b, 104c, 104d, 104e and an insole for collecting and transmitting data sensed at the plurality of target points 104a-104e ( insole) node 106, first means 108 for coupling data to network 110, and second means 112 for coupling the data to collector node 114 and then to computer 116.

  FIG. 3 shows a portion of the sensing system 100 shown in FIG. 1 and an exploded transducer 300 thereby. The insole of the sensing system 100 includes a foot force transducer 300 that may include a continuous capacitive pressure sensor system. A conventional foot force transducer is a discrete array formed by stacking two sets of electrically conductive strips (strips) side by side in an orthogonal direction on both sides of a central layer of a three-layer structure. Has a capacitor.

  Unlike such conventional transducers, the sensing system 100 design allows for flexible placement of conductive elements when creating a typical three-layer structure. A continuous capacitive pressure sensor element at the insole of the shoe is made using a conductive polymer 302 that is variable, that is, the conductivity changes with the detected pressure. The conductive polymer 302 is disposed between conductive traces or lines 304, 306 of conductive material on flexible circuit sheets 308, 310 made of flexible polymer film. The polymer film is laminated to a copper sheet that has been etched to give a conductor pattern. This polyimide film has high heat resistance, dimensional stability, good dielectric strength, and high flexibility, so that it can withstand harsh environments.

  The continuous resistance / capacitance sensor layer may be an extruded, ultra-high density conductive XPU (cross linked polyurethane) foam of the electrostatic discharge (ESD) type. This material is used to protect against ultra-high voltage electrostatic discharge (ESD) and is a compressible form factor to protect physical devices from motion shocks. ) As shown in FIG. 6, the material has linear resistance characteristics and static characteristics in the compression force range (0-30 psi) (where 1 pound is about 453.6 grams and 1 inch is about 2.54 cm). Provides capacitance characteristics.

The XPU foam used in layer 302 is a semiconductor whose characteristic impedance changes in response to applied pressure or compressive force. As shown in FIG. 6, the impedance characteristics of the material are non-linear when the applied pressure (eg, less than 10 psi) or compressive force is low, and become linear as the applied pressure or compressive force increases. The thickness of the XPU material is also a decisive factor for the impedance characteristics of the XPU material. The impedance function is characterized as follows:
When 0 ≦ p ≦ Pc, Z (p) XPU = [R (p) + jwC (p)] (1-exp (−p / Rc))
When Pc <p <Pmax, Z (p) XPU = R (p) + jwC (p)
When Po <p <30 psi Po = Pc * n * 0.125, Z (p) XPU? R (p)
Where n = number of XPU layers (ie, thickness = 0.125 inches, where 1 inch is 2.54 cm), and P is the operating pressure starting linearly. The characteristic impedance of the XPU material may be algorithmically profiled by embedded software running on the sensing system 100 processor.

  Variable pressure analysis point technology, ie, variable pressure analysis point technique, can be used to dynamically map multiple points / regions for foot pressure measurement . For example, referring again to FIG. 1, a portion of the heel region 104a and toe regions 104c, 104d can be measured for about 10 milliseconds while the arch region 104e can be measured for 25 milliseconds. By this measurement, for example, in the case of a person suffering from diabetes who does not notice that a certain region of the foot is inflated due to nerve damage caused by a disease, pattern measurement becomes possible. By using targeted pattern measurements, a warning can be generated if there is a change in the variation in the foot pressure at the sole.

  It is contemplated that other materials may be used such as piezoceramic materials that can provide a capacitive effect, a piezoelectric effect, and / or a resistive effect.

  The transducer 300 of the sensing system 100 incorporates these modular, lightweight, high resolution continuous pressure sensing shoe insoles that can be reconfigured in various configurations and details via the RF module 312. Pressure data is wirelessly transmitted to the computer 116, which collects and displays the data collectively. Sensing system 100 may be integrated with other systems (eg, vision-based sensing systems) to provide a robust multimodal sensing capability. Therefore, the sensing system 100 not only provides a series of applications for data analysis / visualization, data recording and playback, but also groups a plurality of sensing devices into a cluster that transmits data in real time to a computer. Sometimes it forms.

  The sensing system 100 detects changes in the electrical properties of these continuous capacitance pressure sensors due to mechanical deformation of the material. Since the sensing system typically has a recording duration of about 1 second at a sampling rate of 50 Hz for a transducer 300 that includes 200 elements or sensors, the pressure data detection point is one per transducer. Approximately 10,000 points per second. Because of this amount of information, visual display and data organization techniques can be used. A graph display of the pressure distribution is expressed by a device 314 connected by wires shown in the figure. These pressure maps are acquired at each sampling interval or at specific instants while the foot is in contact with the ground. A graphical representation 316 of peak pressure can be used to display the contact manner of the individual foot with the ground. This image can be generated by showing this maximum pressure, since the maximum pressure under the foot always occurs during ground contact.

  The sensing system 100 can measure plantar pressure while standing on two legs, and the biped increases the toe pressure about 2.6 times higher than the forefoot pressure. The highest forefoot pressure is below the second and third metatarsal heads. While standing, the toes have little function to share the load. The plantar peak pressure is not substantially related to body weight. Sensing system 100 measures foot pressure during biped standing, walking and running, and determines that the highest pressure under the forefoot is below the third metatarsal head. Show. When standing on two feet and walking, the peak pressure below the third metatarsal head is significantly higher than the pressure below the other metatarsal head. During the impact phase of the reaction force from the ground when running, that is, during the period of impact, the foot collides with the ground, so the momentum of the decelerating limb changes abruptly, and as a result, the transient force is Transmitted to the skeleton. These forces reach up to three times the weight. Repeated transmission of these forces results in degradation and overuse injury. Sensing system 100 that measures plantar pressure distributed across the sole of the foot while running (running), by virtue of its ability, as a result of the reaction force from the ground during the impact phase, the biomechanics of the foot. By profiling the physical characteristics, it is possible to determine the likelihood of degeneration and overuse injury early, ie very quickly.

FIG. 4 shows in schematic format an electrode grid selector mapping means 400 that may be used with the converter shown in FIG. Grid selector mapping means 400 may include a combination of logic, firmware, and hardware in a suitable microcontroller. The transducer 300 includes a three layer conductive foam 302 between electrode grids (not shown in FIG. 4) on sheets 308, 310. Such a three-layer structure is electrically coupled between + _VCC and ground by bias resistor 402. Vfout from sheet 308 is an input to a 10-bit analog-to-digital converter (ADC) 406, which then outputs from a 10-bit digital output terminal.

  FIG. 5 shows in a schematic format a microcontroller 500 incorporating the electrode grid selector mapping means shown in FIG.

  At startup, the sensing system 100 first determines whether this system is a collector node or collection node 114 or an insole node 106. The sensing system makes this determination by first determining whether any wired interface exists. Since the USB interface is to allow connection to the computer 116, there is a wired interface when the sensing system 100 is the collector node 114.

  As collection node 114, sensing system 100 initializes MCU (microcontroller unit), COP (coprocessor), GPIO (general-purpose input / output unit), SPI (serial peripheral interface), IRQ (interrupt request), and A desired RF transceiver clock frequency is set by a calling routine of MCUInit, GPIOInit, SPIInit, IRQInit, IRQACK, SPIDrvRead, and IRQPinEnable. MCUInit is a master initialization routine that turns off MCU monitoring (watchdog), sets a timer module, and uses BUSCLK as a reference that is pre-scaled in 32 steps. Set the state variable gu8RTxMode to SYSTEM_RESET_MODE and call the routines GPIOInit, SPIInit and IRQInit. Next, set the state variable gu8RTxMode to RF_TRANSCEIVER_RESET_MODE and check IRQFLAG to see if IRQ has been asserted. After the RF transceiver interrupt is first cleared using SPIDrvRead, the RF transceiver is checked for an ATTN (Attention) IRQ interrupt. As the final step of MCUInit, PLMEPhyReset (to reset the physical MAC layer), IRQACK (to acknowledge (ACK) pending IRQ interrupts) and IRQPinEnable (on the negative edge of the signal, pin IE, IRQ CLR) A call is made to enable (Pin Enable).

  Once the collector node processing is initialized, the sensing system 100 can receive RF packets from the insole node 106 at any time. This is initiated by creating an RF packet receive queue that is driven by the RF transceiver packet receive interrupt recall function. When an RF packet is received from the insole node 106, a check is first made to determine whether the packet is from a new insole node 106 or an existing insole node. If this is from an existing insole node 106, the sequence number of the RF packet is checked to determine continuous synchronization before further analyzing the packet. If this is from a new insole node 106, a context state block for the insole node is created and initialized. Following this node-to-node RF packet session level processing, the RF packet data payload is analyzed. This payload includes a compressed plantar foot pressure profile based on the current variable pressure analysis map. The first portion of the compressed data includes a map mask array configured as follows.

  Here, the bits of the FootMaskArray (row 1, row 2,..., Row m) are set to 1 for data of value 255. Each row's representation byte uses 6 bits (ie, the most significant 2 bits are zero and are reserved for future use), each A / D channel (the current utility has 6) Refer to The FootRowMask [k] array is then scanned for inactive values (uncompressed). The position in the FootRowMask [k] array that sets the bits of the uncompressed value is determined. This is done by first finding which of the 16 bytes (representing a row) of the FootRowMask [k] array is a row with an uncompressed value. It then removes the base value taken into the bytes of the subject row and uses the rest as an XOR and bitmask with existing content that can be other uncompressed values already identified.

  Once the RF packet from the insole node 106 is decompressed or decompressed, the collector node 114 uses the SCITransmitArray routine to extract the decompressed RF packet data (gsRxPacket.pu8Data and gsRxPacket.u8DataLength) to the USB interface (not shown). To the computer 116 connected via the computer. Insole pressure data is formatted as follows.

  The IEEE 802.15.4 standard (hereinafter referred to as “802.15.4”), which is the base of ZigBee, WirelessHART, and MiWi specifications, specifies a maximum packet size of 127 bytes, and Time Synchronized Mesh Protocol (TSMP) is Allocate or reserve 47 bytes for operation, leaving 80 bytes for payload. The 2.4 GHz industrial scientific medical (ISM) radio frequency (RF) band transceiver that can be used here is compliant with 802.15.4. It includes a complete 802.15.4 physical layer (PHY) modem designed for the 802.15.4 wireless standard that supports peer-to-peer, star and mesh networks. In accordance with various embodiments of the present invention, it is combined with an MPU to create the necessary wireless RF data links and networks. A transceiver (eg, RF module 312) supports 250 kbps O-QPSK (O-QPSK) data and full spread spectrum encoding and decoding of a 5.0 MHz channel.

  Full control, eg, status reading, data writing, and data reading, is performed by the RF transceiver interface port of the sensing system node device. The MPU of the sensing system node device accesses the RF transceiver of the sensing system node device via an interface “transaction” in which multiple bursts of byte-length data are transmitted over the interface bus. Each transaction has a length of 3 bursts or more depending on the type of transaction. A transaction is always a read or write access to a register address. The associated data for accessing any one register is always 16 bits long.

  The reception mode is a state in which the RF transceiver of the sensing system node device is waiting for an incoming data frame. The packet reception mode enables the RF transceiver of the sensing system node device to receive the entire packet without interference with the MPU of the sensing system node device. All packet payloads are stored in RX Packet RAM and the microcontroller retrieves data after determining the length and validity of the RX packet.

  The RF transceiver of the sensing system node device is waiting for a preamble followed by a start of frame delimiter. From there, the length of the frame is determined using a frame length indicator and a cyclic redundancy check (CRC) sequence is calculated. After receiving the frame, the sensing system node device application determines the validity of the packet. Due to noise, it is possible to report invalid packets under any of the following conditions: Condition: Valid CRC with frame length (0, 1 or 2) and / or Invalid CRC with invalid frame length.

  The application software of the sensing system node device determines whether or not the CRC of the packet is valid, and whether or not the packet frame length of 3 or more is valid. In response to an interrupt request from the RF transceiver of the sensing system node device, the MPU of the sensing system node device determines the validity of the frame by reading and checking the valid frame length and CRC data. The receive packet RAM port register is accessed when the sensing system node device's RF transceiver is read for data transfer.

  The RF transceiver of the sensing system node device transmits all packets without interference from the MPU of the node device of the present invention. All packet payloads are pre-loaded into the TX Packet RAM and the RF transceiver of the sensing system node device transmits the frame, after which the complete status of transmission complete is set in the MPU of the sensing system node device. When the packet transmission is successful, a transmission interrupt routine executed by the MPU of the sensing system node device reports the completion of the packet transmission. In response to an interrupt request from the RF transceiver of the sensing system node device, the MPU of the sensing system node device reads the status to clear the interrupt and checks for successful transmission.

  Control and data transfer of the RF transceiver of the sensing system node device is achieved by a serial peripheral interface (SPI). While the normal SPI protocol is based on 8-bit transfers, the RF transceiver of the sensing system node device requires a higher level transaction protocol based on multiple 8-bit transfers per transaction. A single SPI read or write transaction consists of an 8-bit header transfer followed by two 8-bit data transfers. The header represents the access type and the address of the register. Subsequent bytes are read or write data. The SPI also supports recursive “data burst” transactions where additional data transfers can occur. The recursive mode is mainly intended for packet RAM access and rapid configuration of the RF transceiver of the sensing system node device.

  When the sensing system determines whether to operate in insole mode, it resets its state flag FootStepPacketRecvd and calls its MLMERXEnableRequest routine while enabling the LOW_POWER_WHILE state. The insole node 106 waits 250 milliseconds for a response from the collector node 114 to determine whether a default full insole scan or a map electrode scan is initiated as a default condition. . For a map electrode scan, the collector node transmits the appropriate electrode scan mapping configuration data. The electrode scan is performed by the FootScan routine. In the FootScan routine, the FootDataBufferIndex is initialized and the row is activated by enabling the MCU direction mode for output [PTCDD_PTCDDN = Output] and lowering the associated port line [PTCD_PTCD6 = 0] That is, it is activated. As each row is activated based on an electrode scan map, a column attached to the MCU analog signal port samples and reads the current voltage of each of the column lines, and the read voltages Is converted to a digital value that is the plantar foot pressure across the selected row. All rows are scanned continuously and the entire process is repeated until a reset condition or inactive power down mode.

  The plantar foot pressure data is compressed by clearing a bitmap mask array configured as follows.

  This is where the FootMaskArray [k] bit is set to 1 for data without value compression. Each row's representation byte uses 6 bits (ie, the most significant 2 bits are zero and are reserved or reserved for future use) to reference each A / D channel (there are 6). To set the compression bit, the routine FootSetMask is called with the corresponding parameters FootRowMaskIndex and MaskValue set, and then an XOR operation is performed on FootRowMask [R] with the selected mask value based on MaskValue { 0x01; 0x02; 0x04; 0x08; 0x10; 0x20;

  Using some variables such as FootSendNumBytes and FootDataBufferIndex, prepare 802.15.4 RF packet gsTxPacket.gau8TxDataBuffer [] and send it using the compressed data of FootDataBuffer []. An RF packet is transmitted using an RFSendRequest (& gsTxPacket) routine. This routine checks whether gu8RTxMode is set with IDLE_MODE and calls the RAMDrvWriteTx routine using gsTxPacket as a pointer, which then calls SPIDrvRead to read the register contents of the RF transceiver's TX packet length. Using this content, the mask length setting is updated by 2 by adding 2 to the CRC and 2 to the code byte. Call SPIDrvWrite to update the TX packet length field. Next, SPIClearRecieveStatReg is called to clear the status register, and then SPIClearRecieveDataReg is called to clear the received data register, making the SPI interface ready for reading or writing at any time.

  When the SPI interface is in the ready state, SPISendChar is called which transmits an OxFF character representing the first code byte. Next, SPIWaitTransferDone is called to verify whether transmission has been performed.

  Here, SPISendChar is called again to transmit the second code byte, 0x7E byte. Furthermore, SPIWaitTransferDone is called again to verify whether transmission has been performed. While these code bytes are being transmitted, the remainder of the packet is sent to a series of sequential SPISendChar, SPIWaitTransferDone, SPIClearRecieveDataReg using a for loop where psTxPkt-> u8DataLength + 1 represents the number of iterations. Once this is done, the RF transceiver is loaded with the packet to transmit. ANTENNA_SWITCH is set to transmit, LNA_ON mode is enabled, and finally RTXENAssert is called to actually send the packet.

  Thus, by using a continuous two-dimensional pressure sensing grid with variable mapping capability, three-dimensional real-time plane pressure can be obtained and transmitted wirelessly to a remote location for analysis and display. it can. Further details regarding programming of the sensing system 100 as described above can be found in “Wireless Sensing Triple Axis Reference Design Designer Manual”, Document Number ZSTARRM, Revision 3, January 2007, And “Simple Media Access Controller (SMAC) User's Guide” document number SMACRM, revision 1.2, April 2005. Each of these is a publication of Freescale semiconductor, Inc., which is incorporated herein by reference.

  Referring now to FIG. 8, a first electrode grid layer 800 of a transducer according to another embodiment of the present invention is shown. The layer 800 corresponds to the layer 308 illustrated in FIG. However, in this case, a plurality of transverse grid members 802 are electrically coupled to the RF module 312, such as a plurality of longitudinal grid members 804.

  FIG. 9 shows a second electrode grid layer 900 for use with the first electrode grid layer 800. The layer 900 corresponds to the layer 310 shown in FIG. However, in this case, a plurality of longitudinal members 902 are coupled to the RF module 312 to cooperate with the first electrode grid layer 800 and the conductive foam layer 302 (not shown in FIG. 8 or FIG. 9); Pressure is sensed at a plurality of target points along the user's foot.

  FIGS. 10A-10F show in schematic format portions of an RF module 312 that may be used with the first and second electrode grid layers shown in FIGS. FIG. 10A shows a portion of a schematic diagram for a flexible PCB connection 1000. Electronic grid rows and columns in the map array may be coupled to the RF module 312. FIG. 10B shows a portion of a schematic diagram relating to the battery 1002. A suitable battery is model BK-877, having a phosphor bronze CR2450 button battery retainer (Coin Cell Retainer) SMD, a nickel finish contact, and a Mylar battery insulator.

  Referring now to FIG. 10C, a portion of a triaxial accelerometer 1004 according to an embodiment of the invention is schematically shown. One exemplary accelerometer 1004 is model MMA7260QT ± 1.5 g-6 g 3-axis low g micromachined accelerometer (Three, manufactured by Freescale semiconductor, Inc. (Tempe, Arizona USA). Axis Low-g micromachined accelerometer). This low-cost capacitive micromachine accelerometer features signal conditioning, a single pole low pass filter, temperature compensation, and a g selection that allows you to choose from four sensitivities. Zero-g offset full scale span and filter cutoff are factory settings and do not require external equipment. The accelerometer includes a sleep mode that is ideal for handheld battery-powered electronics.

  The accelerometer 1004 is an integrated circuit accelerometer obtained by surface micromachining. The device consists of two capacitive sensing cells (called g-cells) obtained by surface micromachining and a signal conditioning ASIC contained in a single integrated circuit package. The sensing element is sealed at the wafer level using a cap wafer obtained by bulk micromachining.

  A g-cell is a mechanical structure formed from a semiconductor material (polysilicon) using a semiconductor process (masking and etching). This can be modeled as a set of beams attached to a movable central mass that moves between fixed beams. As the system is accelerated, the movable beams are deflected from their rest position.

  As the beam attached to the central mass moves, the distance from one beam to the fixed beam on one side increases by the same amount as both the decrease in the distance to the fixed beam on the other side. The change in distance is a measurement of acceleration.

  The g cell beam forms two back-to-back capacitors. As the center beam is accelerated and moved, the distance between the beams changes and the value of each capacitor changes (C = Aε / D). Where A is the area of the beam, ε is the dielectric constant, and D is the distance between the beams.

  ASIC uses switched capacitor technology to measure g-cell capacitors and extracts acceleration data from the capacitance difference between the two capacitors. The ASIC also adjusts the signal and filters the signal (with switched capacitor technology) so that the ratiometric, i.e. sensitivity and offset, is linearly dependent on the supply voltage and proportional to the acceleration. Resulting in a level output voltage.

  The g-select function allows selection from the four sensitivities present in the device or accelerometer. Depending on the logic input at pins 1 and 2, the internal gain of the device changes to function with 1.5g, 2g, 4g or 6g sensitivity (see Table 1 below). This feature is ideal when the product or accelerometer has an application that requires different sensitivities for optimum performance. Sensitivity can be changed at any time during product operation. The g-select 1 and g-select 2 pins remain unconnected (800 mV) for applications that require only 1.5 g sensitivity if the device has an internal pull-down to maintain that sensitivity. / G).

  The accelerometer 1004 may provide a sleep mode that is ideal for battery powered products. When the sleep mode is active, the device or accelerometer output is turned off, significantly reducing the operating current. Applying a low level input signal (sleep mode) to pin 12 puts the device in this mode and reduces the current to typically 3 μA. In order to reduce power consumption, it is recommended to set g selection 1 and g selection 2 to 1.5 g mode. By applying a high level input signal to pin 12, the device resumes and enters normal mode operation.

  The accelerometer 1004 also includes an on-board single pole switched capacitor filter. Since the filter is implemented using switched capacitor technology, no external passive components (ie, resistors and capacitors) are required to set the cutoff frequency.

  Ratiometricity simply means the output offset voltage, and the sensitivity scales linearly with the applied supply voltage. That is, as the supply voltage increases, the sensitivity and offset increase linearly; as the supply voltage decreases, the offset and sensitivity decrease linearly. This is an important feature when interfacing with a microcontroller or A / D converter. This is because the error caused by the supply in the analog-digital conversion process is canceled at the system level. The offset ratiometric error can typically be> 20% at VDD = 2.2V. The ratiometric error of sensitivity can typically be> 3% at VDD = 2.2V.

  The VDD line should have the ability to reach 2.2V in <0.1 ms when measured at the device's VDD pin. Longer rise times will probably interfere with the start-up operation. The physical coupling distance of the accelerometer to the microcontroller needs to be minimal. A flag or die pad on the underside of the package is connected to the ground internally. It is not recommended to solder the flag. A ground plane is placed under the accelerometer 1004 to reduce noise. It is necessary to attach the ground plane to all open terminals. An RC filter with a 1.0 kΩ resistor 1006 and a 0.1 μF capacitor 1008 can be used on the output side of the accelerometer 1004 to minimize clock noise (from the switched capacitor filter circuit). The power and ground PCB layout should not couple power noise. Accelerometers and microcontrollers should not be high current paths. The A / D sampling rate and any external power supply switching frequency must be selected so as not to interfere with the sampling frequency of the internal accelerometer (11 kHz relative to the sampling frequency). This avoids aliasing errors. PCB layout should not have traces or vias under the QFN part. These can cause a ground short to the accelerometer flag.

  Further details regarding accelerometer 1004 can be found in Freescale Semiconductor document number: MMA7260QT, Revision 5, 03/2008, which is incorporated herein by reference.

  Referring now to FIGS. 10D-10F, there is shown a schematic diagram of portions associated with a microcontroller 1010 and a transceiver 1012 including a balun 1014 and a crystal oscillator 1016 that can be used in accordance with embodiments of the present invention. One exemplary platform that incorporates both functions is a microcontroller from the IEEE® 802.15.4 standard and Freescale semiconductor, Inc. (Tempe, Arizona USA). Model MC13213ZigBee (TM) -Compliant Platform-2.4GHz Low Power Transceiver.

  The MC1321x family is Freescale Semiconductor's second generation ZigBee platform, which combines a low power 2.4GHz radio frequency transceiver and 8-bit microcontroller in a single 9x9x1mm 71-pin LGA package. Incorporated. The MC1321x solution can be used for wireless applications from simple dedicated point-to-point connections to full ZigBee mesh networks. The combination of radio and microcontroller in a small footprint package allows for a cost effective solution.

  The MC1321x includes an RF transceiver that is wireless in accordance with 802.15.4 operating in the 2.4 GHz ISM frequency band. The transceiver includes a low noise amplifier, a nominal output power of 1 mW, a PA with an internal voltage controlled oscillator (VCO), integrated transmission / reception, and decoding. The MC1321x also includes a microcontroller based on the HCS08 family of microcontroller units (MCUs), particularly HCS08 version A, and may provide up to 60 KB of flash memory and 4 KB of RAM. The on-board MCU enables a communication stack and also allows applications to reside in the same system-in-package (SIP). MC13213 includes 60K flash memory and 4KB RAM and is also used with Freescale Semiconductor's fully compliant 802.15.4 MAC and fully ZigBee compliant Freescale BeeStack Is intended.

  FIGS. 11 and 12 show first and second algorithms that may be used with the transducers according to FIGS. 8, 9 and 10A-10F. The sensing system 100 uses an exponential moving average filter in conjunction with a sliding window boxcar integrator to process all 3D Ax, Ay, and Az real-time acceleration data. Each can be digitized. Accumulated acceleration data can be analyzed to identify unique motion artifacts such as strides and steps and their individual directions. A reference frame may be created to provide a variable time sequence of motion artifacts. XPU conductive foam (foam) allows reference frames such as the beginning of a step (ie standing posture-starting to slide with the foot raised) and the end of the step (ie lowering the foot-standing posture) Gating becomes possible. A general algorithm that can be incorporated and implemented as embedded software running on a processor that supports the sensing system 100 is as follows.

  [0093] An alternative embodiment of the algorithm is shown in FIG. In either case, the results of these algorithms are summed together as shown in FIG. The formula for this is roughly as follows:

  Sensing system 100 is therefore sensitive enough to measure the difference in plantar pressure between an adult male foot pressure and a female foot pressure under the longitudinal footbow. Under the midfoot, women have lower peak foot pressure while standing. Also, in the case of women, there is a correlation between weight and foot pressure under the longitudinal arch of the woman's foot when walking. This allows the sensing system 100 to analyze the ligament structure, that is, the structure of the ligament that will cause the longitudinal arch to collapse to some extent during the phase of supporting the weight while walking. Become.

  Sensing system 100 can perform similar foot function analysis while running. Specifically, the sensing system 100 can analyze the midfoot load, as well as the amount of rotation of the hind legs that is more apparent for female runners compared to male runners. For children, unlike adults, weight has been found to have a significant impact on the magnitude of pressure under the child's feet, and the foot pressure, or relative, between boys and girls There is no difference in the typical load pattern. In such cases, sensing system 100 may be used periodically to analyze potential problems associated with the child's walking / running / gait as the child grows up. This can provide data to help develop appropriate in-soles and other support structures, and can help renormalize issues related to walking / running / gaiting.

  Sensing system 100 can help determine the cause of pain and leg discomfort in overweight and obese people. Pain and lower limb discomfort can also be found by the ability of the system to analyze plantar pressure analysis. The difference in plantar pressure between obese and non-obese adults while standing and walking increases the ratio of forefoot width to foot length in overweight persons It shows that. This is because the forefoot part has spread under conditions in which the load due to weight has increased. Even if the contact area supporting the foot load on the ground has increased, overweight persons can still stand on their feet on the lower side of the heel, midfoot and forefoot while standing, walking and running. The club pressure is quite high.

  Sensing system 100 measures higher foot pressure under the midfoot during standing periods in obese women than in obese men. As a result of the natural reduction of the original strength of the ligaments in the female foot, the arch flattenes, but this flattening mainly has an effect on body weight. Body weight can affect the pain and discomfort of the legs of these obese people, as well as the choice of footwear for the obese people and their desire to be involved in daily life activities such as walking and running. When walking, forefoot pressure as well as forefoot contact area is significantly increased in obese women. The sensing system 100 can analyze and monitor this increase in forefoot plantar pressure. This increased pressure most often causes discomfort to the foot and prevents these obese women from performing normal physical activity.

  Sensing system 100 can help runners manage injuries due to overuse. Overuse injuries occur every year in more than half of runners who are active, causing them to stop running. Causes of such injuries include variation (difference) or distribution in body dimensions to optimize training variables, hindfoot movement variables, kinematic variables and strength variables. Identifying and analyzing biomechanical parameters, such as real-time foot pressure, by sensing system 100 identifies key athletic footwear properties that protect against overuse injury and improve performance. To help. Such parameters are midsole material properties, which can provide information on variations in footwear manufacture.

  Sensing system 100 may measure and record rear foot rotation, foot pressure patterns, and shock absorption characteristics of running shoes / athletic footwear to help reduce the risk of overuse injuries. Can be analyzed. Therefore, the sensing system 100 can be used to assess whether a shoe fits and the comfort of the shoe during running on various terrain types. The long-term monitoring and archiving capabilities of the sensing system make it possible to analyze the deterioration of shoe characteristics over time and over time.

  Sensing system 100 records the pressure in a shoe during running and training in real time, and information regarding the interaction between the footwear and the structure of the foot of the person wearing the footwear (mechanics). I will provide a. Too much rotation during running and training causes many overuse injuries. In general, by limiting excessive movement of the rear foot and improving shock absorption, the risk of injury in running and training can be reduced. Determining and measuring the rotation of the subtalar joint is important for evaluating running shoes and training shoes. Collecting rotation measurement data of the subtalar joint in real time is one of the main functions of the sensing system.

  Sensing system 100 may determine scratches or fraying and tear and tear by monitoring and recording and evaluating features. The sensing system detects and collects or records foot pressure data wirelessly and in real-time with changes in hindfoot movement combined with differences in mid-sol or mid-sole characteristics. And analyze and have the ability to determine differences in shoe cushions and classify the overall stiffness or stiffness of the shoe. These rigid features change the landing pattern of the footwear and draw out lower impact forces. This allows the wearer to use such shoes to perform a useful biomechanical assessment to minimize injury caused by repeated impact loads. Insole wear is displayed on the outside of the shoe as a green, yellow, and red graphic display display to indicate the degree of wear on the shoe.

  Sensing system 100 may perform weight and force assessment by foot zones (heel, midfoot and forefoot). Sensing system 100 includes foot pressure data related to the vertical ground reaction force pattern and material properties of a running shoe with an advanced cushioning column system during walking, running and / or training. Have the ability to detect, collect and analyze the data wirelessly and in real time.

  The sensing system 100 can determine the gait change / pattern of the subject (subject) during a particular event and between multiple correlated events (practice versus game activity). A change in the pressure pattern of the foot sole can be detected. It is possible to detect even slight fluctuations in pressure over time, for example due to loss of body fluids or fluids in a running race. Ability to wirelessly transmit this information to a collection site or monitor.

  Sensing system 100 can detect changes in force patterns during a particular sporting event and calculate force / energy conditions for the expected output. Obtain current expected output versus energy vector analysis.

  The sensing system 100 may send a signal on the subject when it is dancing or kinematic use, such as an interactive dance movement (eg, the subject (subject) is taking the correct steps, and another signal when it is wrong. Monitoring and analysis necessary to learn dance as a game application).

  Sensing system 100 provides the monitoring and analysis necessary for industrial use to identify forbidden entry, such as acceptable personnel movement, hazardous and / or security areas measured against assembly efficiency. Determine the effectiveness of warehouse personnel, such as determining the placement of individual workers to monitor entry into the area (GPS is not very effective inside buildings, especially in warehouse environments, Monitoring and analysis in applications that stimulate employee health care for weight loss and health maintenance.

  Sensing system 100 may augment the game interface and supplement video games such as PlayStation PS3® and XBox 360® gaming consoles. This adds a special dimension on how to interact with video games run on these gaming machines. Foot pressure activity detected while jumping, walking or running is combined with foot orientation and position data to enhance interactivity with normal popular video games and kick or block in fighting games It becomes possible to play a game by intuitively recognizing.

  The back-end server processing option of sensing system 100 collects as a large group of sensing system insole monitors that represent the field of players involved in sports games (eg, football, soccer, and / or basketball, etc.). be able to. This may be implemented as a website for a remote analysis supporting collective review type application. Sensing system 100 is a data that spans a large reference field (sport field, battlefield, long-distance run) by a specific signature for each sole, by a person (two soles), or by a collection of individual soles. Can be collected. Therefore, the sensing system 100 can download all of this information to a web interface that creates a post-event re-simulation that is stored, compared and evaluated by companions playing the game on the web when it arrives in the transmission zone. To do.

  The sensing system back-end server processing option can collect a large group of sensing system insole monitors that represent a field of players involved in sports games (eg, football, soccer, and / or basketball, etc.). This allows a game strategy analysis program to be created by using correlation analysis using real-time and archived in-sole data. One skilled in the art will readily appreciate that additional data entry, such as real-time video, enables enhanced dynamic game strategy coordination programs and the like.

  Sensing system 100 can be used to indicate water loss during a running race, changes in blood pressure in a medical or rehabilitation environment, blood pressure during a work process (eg, driving a car) that can indicate whether the blood pressure is suitable for the operator to continue. It is possible to detect slight variations in foot pressure over time due to conditions such as changes in Using the monitoring and archiving capabilities of sensing system 100, the program may be configured to manage long-term foot pressure variability analysis as described above.

  The sensing system 100 can be implemented in a vehicle floor mat type configuration as the primary mechanism for vehicle speed operation. The sensing system may also be used in applications that support small motor control when an operator is unable to apply pressure to the hand or foot operating system due to injury or a congenital anomaly. In both cases described above, the wireless support of sensing system 100 allows operation with six degrees of freedom.

  Yet another embodiment of sensing system 100 is a system in which energy is “captured”. That is, the piezoelectric fiber composite can convert mechanical energy into electrical energy. Alternative embodiments of the sensing system 100 may be used to take advantage of the properties of such piezoelectric fiber composites. This is because these composites are lighter and more flexible than piezoceramic bulks. Such a piezoelectric fiber composite can produce 50V at a “stepping” frequency of 3 Hz. Thereby, the battery can be charged at a speed of 5 mm amplifier. Piezoelectric fiber composites can be molded from the heel to toes in the insoles of various embodiments of the present invention. The piezoelectric fiber composite may be parallel to store desired power. As a result, the sensing system 100 can take advantage of the plotted and stacked implementation in conjunction with the polyethylene sheet for insole design.

  Such a sensing system 100 comprising a piezoelectric fiber composite is very durable and has a fatigue life of more than 200 million cycles, with no degradation in its piezoelectric properties. The piezoelectric fiber composite used here has a diameter of 250 microns and its length is variable. Charging circuitry can be added to provide voltage limiting and regulation capabilities for battery charging applications. A particular battery technology useful for sensing system 100 is a function of that application. For example, gaming, sports and health monitoring applications may require a rechargeable lithium-polymer (Li-PoIy) battery. In such a case, a 1 mm insole layer of the piezoelectric fiber composite is suitable for recharge mounting of the battery.

  While various embodiments of the invention have been described, it should be understood that they have been presented for purposes of illustration and not limitation. Therefore, the breadth and scope of the present invention should not be limited by any of the above-described exemplary embodiments, but is defined only in accordance with the following claims and their equivalents.

Claims (41)

A transducer for measuring the pressure at each of a plurality of points in a region of interest, and transmission means for transmitting data corresponding to the measured pressure,
The converter
A sensing system comprising a compression layer, and first and second flexible conductive layers with the compression layer disposed therebetween.   The system of claim 1, wherein the transmission means includes a transceiver.   The system of claim 2, wherein the transceiver includes a wireless transceiver.   The system of claim 1, wherein each of the first and second flexible conductive layers includes an electrode grid. 5. The system of claim 4, further comprising a selector for turning on and off selected points of the electrode grid to variably measure pressure from the selected points of the region of interest.   6. The system of claim 5, wherein the selector dynamically turns on and off the selected point of the electrode grid in real time.   The system of claim 1, wherein the plurality of target points includes a plurality of portions of a foot selected from the group consisting of a forefoot region, a middle foot region, and a hindfoot region.   The group further includes one or more of a plurality of ribs, one or more of a plurality of metatarsals, one or more of a plurality of rib joints, a thumb ball of the foot, an arch of the foot, a plantar fascia The system of claim 7, comprising one or more of a plurality of tarsal bones forming the talus, radius and subtalar joints.   The system of claim 1, further comprising a data compressor that compresses the data corresponding to the measured pressure prior to transmission by the transmission means.   The system of claim 1, wherein the transducer is mounted on a shoe sole.   The system of claim 1, wherein the compressible material comprises a compressible conductive foam.   The system of claim 9, wherein the compressible conductive foam comprises a material suitable for electrostatic discharge (ESD).   The system of claim 1, further comprising a computer adapted to receive the transmission data wirelessly and output the received data in a user readable format. further,
An accelerometer adapted to measure the acceleration of the plurality of points within the region of interest;
14. A system according to claim 13, comprising means for transmitting data corresponding to the measured acceleration.   The system of claim 14, wherein the accelerometer is adapted to measure the acceleration of each of the plurality of points in the region of interest along the x-axis, y-axis, and z-axis.   The computer further comprises integration means for integrating the transmitted data corresponding to the acceleration of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis. Item 16. The system according to Item 15.   The integration means is adapted to output data corresponding to the velocity of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis. 16. The system according to 16.   The integration means is adapted to output data corresponding to the displacement of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis. 16. The system according to 16. The computer further includes:
Means for collecting the integrated data; the collected data collected;
17. A system according to claim 16, comprising correlation means for correlating the transmitted data corresponding to the measured pressure.   20. The system of claim 19, further comprising a computer game coupled to a correlation means and adapted to receive the correlation data, and interactively adapting the computer game accordingly.   The system of claim 19, wherein the computer further comprises diagnostic means for interpreting the collected data and correlation data, thereby recommending a change in the location of the plurality of points.   The system of claim 21, wherein the computer further comprises means for designing a corrective instrument for making the recommended changes.   The system of claim 16, wherein the computer further comprises tracking means for interpreting the collected data and correlation data, thereby recommending changes to a training program.   The system of claim 16, wherein the computer further includes tracking means for interpreting the collected data and correlation data, thereby recommending changes to a treatment program.   The system of claim 13, wherein the user readable form includes Extensible Markup Language (XML). A method for sensing a force applied to a first moving object by a second moving object in contact with the first object, comprising:
Measuring the force at each of a plurality of points in a region of interest between the first object and the second object;
Dynamically activating a selected point in the region of interest and variably measuring a force at the selected point in real time;
measuring the acceleration of each of the plurality of points in the region of interest along the x-axis, y-axis, and z-axis;
Transmitting data corresponding to the measured force and the measured acceleration to a computer, the computer being adapted to receive the transmitted data and output the received data in a user-readable format;
Integrating the transmission data corresponding to the acceleration of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis;
Collecting the integrated data; and correlating the collected data with the transmitted data corresponding to the measured force and the measured acceleration.   27. The method of claim 26, further comprising outputting data corresponding to the velocity of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis.   27. The method of claim 26, further comprising outputting data corresponding to the displacement of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis.   27. The method of claim 26, further comprising compressing the data corresponding to the measured force prior to the transmitting step. further,
27. The method of claim 26, comprising: combining a computer game coupled to receive the correlation data; and interactively adapting the computer game according to the correlation data. further,
27. The method of claim 26, comprising diagnostically interpreting the collected data and correlation data; and changing the position of the plurality of points according to the interpretation. further,
Establishing a predetermined motion training program for the plurality of points;
Interpreting the collected data and correlation data diagnostically;
27. The method of claim 26, comprising tracking the interpretation of the collected data and correlation data as a function of time; and changing the predetermined movement of the plurality of points according to the tracked interpretation. further,
Establishing a predetermined motion therapy program for the plurality of points;
Interpreting the collected data and correlation data diagnostically;
27. The method of claim 26, comprising tracking the interpretation of the collected data and correlation data as a function of time; and changing the predetermined movement of the plurality of points according to the tracked interpretation. A computer readable medium containing computer executable instructions comprising:
One or more instructions for measuring force at each of a plurality of points in a region of interest between the first object and the second object;
One or more instructions that dynamically activate a selected point in the region of interest and variably measure the force at the selected point in real time;
one or more instructions for measuring the acceleration of each of the plurality of points in the region of interest along the x-axis, y-axis, and z-axis;
One or more instructions for transmitting data corresponding to the measured force and the measured acceleration to a computer, the computer receiving the transmitted data and receiving the received data The one or more instructions adapted to output in a format;
One or more instructions for integrating the transmitted data corresponding to the acceleration of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis;
One or more instructions for collecting the integrated data; and one or more instructions for correlating the collected data with the transmitted data corresponding to the measured force and the measured acceleration Computer readable medium.   The method further comprises one or more instructions for outputting data corresponding to the velocity of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis. 34. The medium according to 34.   The method further comprises one or more instructions for outputting data corresponding to the displacement of each of the plurality of points in the region of interest along the x-axis, the y-axis, and the z-axis. 34. The medium according to 34.   35. The medium of claim 34, further comprising one or more instructions for compressing the data corresponding to the measured force prior to the transmitting step. further,
35. One or more instructions for combining a computer game coupled to receive the correlation data; and one or more instructions for interactively adapting the computer game according to the correlation data. The medium described in 1. further,
35. The medium of claim 34, comprising one or more instructions for diagnostically interpreting the collected data and correlation data; and one or more instructions for changing the position of the plurality of points according to the interpretation. . further,
One or more instructions for establishing a predetermined motion training program for the plurality of points;
One or more instructions for diagnostically interpreting the collected data and correlation data;
One or more instructions for tracking the interpretation of the collected data and correlation data as a function of time; and one or more for changing the predetermined movement of the plurality of points according to the tracked interpretation 35. The medium of claim 34, comprising instructions. further,
One or more instructions for establishing a predetermined motion therapy program for the plurality of points;
One or more instructions for diagnostically interpreting the collected data and correlation data;
One or more instructions for tracking the interpretation of the collected data and correlation data as a function of time; and one or more for changing the predetermined movement of the plurality of points according to the tracked interpretation 35. The medium of claim 34, comprising instructions.

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