Patent Description:
There has been a conventional bicycle-type exercise instrument in which a pedaling measurement unit attached to the bicycle-type exercise instrument has a rotational speed sensor and that measures cadence, which is the rotational speed of a crank portion, according to an output signal of the rotational speed sensor (see PTL <NUM>, for example).

PTL <NUM>: <CIT>
Furthermore, in the publication "<NPL>, an application for Android-based mobile devices is described that enables a real-time calculation of heart rate and cadence for biking. Therefore, both ECG and EMG data are acquired in real time by Shimmer™ sensors and transmitted via Bluetooth, as well as processed and evaluated on the mobile device. The ECG algorithm is based on the Pan-Tompkins algorithm for QRS-Detection and offers a heart beat detection rate of more than <NUM>%. The EMG algorithm offers a treadle detection rate of more than <NUM>%. The application's range of features is complemented by GPS data for the calenlation of speed and location information.

The invention is specified in the independent claims.

Incidentally, the conventional bicycle-type exercise instrument uses a rotational speed sensor to measure cadence, so the structure is not simple.

Therefore, an object is to provide a cadence measurement device having a simple structure and to provide a cadence measurement method.

A cadence measurement device in an embodiment of the present disclosure includes a myoelectric potential sensor attached to a leg portion of a living body, a waveform processing unit that performs waveform processing to obtain a myoelectric potential waveform from an output signal of the myoelectric potential sensor, and a cadence deriving unit that derives cadence according to the myoelectric potential waveform obtained by the waveform processing.

It is possible to provide a cadence measurement device having a simple structure and to provide a cadence measurement method.

Embodiments to which a cadence measurement device and a cadence measurement method in the present invention are applied will be described below.

<FIG> is a drawing indicating the structure of a cadence measurement device <NUM> in an embodiment. In <FIG>, a smart phone <NUM> is also indicated. In <FIG>, the cadence measurement device <NUM> is indicated more largely than the smart phone <NUM> to indicate the structure of the cadence measurement device <NUM> in detail. However, the actual cadence measurement device <NUM> is smaller and more lightweight than the smart phone <NUM>.

The cadence measurement device <NUM> includes a myoelectric potential sensor <NUM>, a MCU (Micro Control Unit) <NUM>, a communication unit <NUM>, and a battery <NUM>. As an example, the cadence measurement device <NUM> is attached to the thigh of the user who pedals a bicycle or bicycle-type exercise instrument by being stuck with, for example, a tape or the like. Then, the cadence measurement device <NUM> measures cadence. Cadence is a number of revolutions of the crank axis of the pedal per minute. The cadence measurement device <NUM> only needs to measure the myoelectric potential of the surface of the leg portion of the user with the myoelectric potential sensor <NUM>. As an example, the cadence measurement device <NUM> is stuck so as to measure the myoelectric potential of the quadriceps muscle.

The myoelectric potential sensor <NUM> has an analog amplifier circuit and a plurality of bioelectrodes stuck to the thigh of the user. The myoelectric potential sensor <NUM> amplifies a waveform signal, which represents a myoelectric potential detected in a hyperbolic lead method by using the plurality of bioelectrodes, with the analog amplifier circuit, and then outputs the waveform signal. The output of the myoelectric potential sensor <NUM> is an example of an output signal and is input into the MCU <NUM>.

The MCU <NUM> has a main control unit <NUM>, a waveform processing unit <NUM>, a cadence deriving unit <NUM>, and a memory <NUM>. The MCU <NUM> is realized by a microcomputer that includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and the like. The main control unit <NUM>, waveform processing unit <NUM>, cadence deriving unit <NUM> indicate the functions of programs executed by the MCU <NUM> as functional blocks. Also, the memory <NUM> functionally represents a memory in the MCU <NUM>.

The main control unit <NUM> is a processing unit that controls the MCU <NUM> in a centralized manner, and executes processing other than processing executed by the waveform processing unit <NUM> and cadence deriving unit <NUM>. Specifically, the main control unit <NUM> performs A/D (Analog to Digital) conversion processing on the output signal of the myoelectric potential sensor <NUM> to convert the output signal to a digital waveform signal and other processing, for example.

The waveform processing unit <NUM> acquires data representing a myoelectric potential waveform by performing waveform processing on the output signal of the myoelectric potential sensor <NUM>. Waveform processing performed by the waveform processing unit <NUM> will be described later by using <FIG>.

The cadence deriving unit <NUM> derives cadence from the myoelectric potential waveform acquired by the waveform processing unit <NUM>. Waveform processing performed by the cadence deriving unit <NUM> will be described later by using <FIG>.

The memory <NUM> is an example of a storage unit. The memory <NUM> stores programs and data needed by the MCU <NUM> to perform processing as well as other data, and also temporarily stores data to be used by the main control unit <NUM>, waveform processing unit <NUM>, and cadence deriving unit <NUM> in processing and the like.

The communication unit <NUM> is a communication unit in BLE (Bluetooth Low Energy) (registered trademark) as an example, and performs data communication with the smart phone <NUM>. Measurement results of the cadence measurement device <NUM> are transmitted to the smart phone <NUM> through the communication unit <NUM>. Application programs for the cadence measurement device <NUM> are installed in the smart phone <NUM>, as an example. The smart phone <NUM> displays or otherwise processes data that an application program has received from the cadence measurement device <NUM> on the display or the like of the smart phone <NUM>.

The battery <NUM> is a power source that supplies electric power to the myoelectric potential sensor <NUM>, MCU <NUM>, and communication unit <NUM>. The battery <NUM> only needs to be a secondary battery, as an example. The battery <NUM> can be charged in a state in which the battery <NUM> is incorporated into the cadence measurement device <NUM> or is removed from the cadence measurement device <NUM>.

<FIG> are drawings explaining waveform processing executed by the waveform processing unit <NUM>. In <FIG>, the horizontal axis indicates time and the vertical axis indicates amplitude. <FIG> indicates the waveform of a digital waveform signal created by the main control unit <NUM> through A/D conversion. <FIG> indicates part (segment for three seconds) in <FIG> by enlarging it in the horizontal-axis direction. The digital waveform signal indicated in <FIG> represents a myoelectric potential (EMG: ElectroMyoGraphy) but includes noise and the like as well.

<FIG> indicates a component waveform after the waveform processing unit <NUM> has performed band-pass filter processing on the digital waveform signal indicated in <FIG>. Band-pass filter processing is filter processing (waveform processing) to pass only <NUM> to <NUM>, which are in a frequency band that the myoelectric potential waveform can take in the digital waveform signal, and remove components at lower than <NUM> and components at higher than <NUM>.

<FIG> is a drawing indicating a myoelectric potential waveform obtained when the waveform processing unit <NUM> performs waveform processing on the component waveform indicated in <FIG>. By performing waveform processing to convert the amplitude of the component waveform indicated in <FIG> to a signal waveform with RMS (Root Mean Square) values, the myoelectric potential waveform indicated in <FIG> is obtained. The myoelectric potential waveform is obtained by squaring the positive component and negative component of the component waveform indicated in <FIG> and taking a square root.

<FIG> is a drawing indicating a myoelectric potential waveform that the waveform processing unit <NUM> obtains by performing low-pass filter processing on the myoelectric potential waveform indicated in <FIG>. It is said that the number of revolutions per minute when a human pedals a bicycle is <NUM> rpm (revolutions per minute), which is about <NUM>, or less. Therefore, to extract components at <NUM> or lower from the myoelectric potential waveform indicated in <FIG>, low-pass filter processing in which <NUM> is used as the cut-off frequency is performed.

<FIG> is a drawing explaining processing executed by the cadence deriving unit <NUM>. In <FIG>, the period T is a three-second period in the myoelectric potential waveform. Since it is thought that the period T includes a plurality of cycles during which the user pedals, the period T is set to three seconds as an example.

The cadence deriving unit <NUM> obtains the average value A of amplitude data in the period T, and divides the period T into a plurality of cycles with the amplitude center of the myoelectric potential waveform in the period T taken as the average value A. In <FIG>, three cycles T1, T2, and T3 are included in the period T. There is a residual, which is shorter than one cycle, before cycle T1. The cadence deriving unit <NUM> obtains periods T1, T2, and T3.

<FIG> is drawing indicating table data that relates cadence and the period (ms (milliseconds)) of one cycle to each other. The table data indicated in <FIG> is data that relates the period of one revolution (period of one cycle) of cadence used as the number of revolutions of the crank. As an example, <FIG> indicates the period (<NUM> to <NUM>) of one cycle when cadence is <NUM> to <NUM> (revolutions/minute).

The cadence deriving unit <NUM> references the table data and derives the cadence for which the period of one cycle is closest to each of periods T1 to T3. As a result, it will be assumed as an example that the cadence deriving unit <NUM> has derived that cadence in period T1 is <NUM> (revolutions/minute), cadence in period T2 is <NUM> (revolutions/minute), and cadence in period T3 is <NUM> (revolutions/minute). The cadence measurement device <NUM> obtains cadence from the myoelectric potential waveform in the way described above.

<FIG> is a flowchart indicating processing executed by the cadence measurement device <NUM>. As a premise, it will be assumed that the cadence measurement device <NUM> has been stuck to the thigh of the user, the power supply of the cadence measurement device <NUM> is turned on, and the myoelectric potential sensor <NUM> is performing measurement of the myoelectric potential. Processing indicated in <FIG> is processing realized by the cadence measurement method in an embodiment.

The main control unit <NUM> performs processing in which A/D conversion processing is performed on the output signal of the myoelectric potential sensor <NUM> to convert the output signal to a digital waveform signal (step S1). More specifically, as an example, the main control unit <NUM> creates a digital waveform signal by performing A/D conversion on the output signal of the myoelectric potential sensor <NUM> at a sampling cycle of <NUM>, and stores amplitude data of the digital waveform signal in the memory <NUM>.

The waveform processing unit <NUM> decides whether at least a predetermined number of amplitude data items of the digital waveform signal have been accumulated (step S2). Here, at least the predetermined number of amplitude data items of the digital waveform signal refer to amplitude data items of the digital waveform signal for three seconds or more, as an example. This is because the periods of a plurality of cycles included in the period T for three seconds will be obtained later as in <FIG>.

If the waveform processing unit <NUM> decides that at least the predetermined number of amplitude data items of the digital waveform signal have been accumulated (S2: YES), the waveform processing unit <NUM> performs band-pass filter processing on the digital waveform signals (step S3). Due to this, component waveforms after only <NUM> to <NUM>, which are in a frequency band that the myoelectric potential waveform can take, in the digital waveform signal has been passed are obtained as indicated in <FIG>. Incidentally, if the waveform processing unit <NUM> decides in step S2 that at least the predetermined number of amplitude data items of the digital waveform signal have not been accumulated (S2: NO), the waveform processing unit <NUM> returns the flow to step S1. This is because the waveform processing unit <NUM> waits for amplitude data to be further accumulated.

The waveform processing unit <NUM> performs waveform processing to convert the amplitude of the component waveform to a signal waveform with root mean square (RMS) values (step S4). Due to this, a myoelectric potential waveform as indicated in <FIG> is obtained.

The waveform processing unit <NUM> performs low-pass filter processing on the myoelectric potential waveform (step S5). Due to this, out of the myoelectric potential waveforms obtained in step S4, components at <NUM> or lower are extracted and a myoelectric potential waveform as indicated in <FIG> is obtained.

The cadence deriving unit <NUM> calculates the average value A of amplitude data in the period T (step S6). The period T (see <FIG>) is a period that includes at least the predetermined number of amplitude data items of the digital waveform signal, which have been obtained in step S2. That is, the period T is determined in step S2.

The cadence deriving unit <NUM> measures the period of each cycle included in the period T (step S7). As an example, processing in step S7 is processing to measure a plurality of periods T1, T2, and T3 included in the period T, as described by using <FIG>. Measurement of periods T1, T2, and T3 only needs to be performed by obtaining an interval between sampling points, at which the amplitude data of the myoelectric potential waveform becomes the same as the average value A, in the direction of time. In this case, if there is no sampling point, at which a match with the amplitude data of the average value A is found, in the myoelectric potential waveform, interpolation or the like only needs to be performed for two sampling points between which the average value A is interposed.

The cadence deriving unit <NUM> references the table data and derives the cadence for which the period of one cycle is closest to each of periods T1 to T3 (step S8).

The main control unit <NUM> causes the communication unit <NUM> to transmit data representing cadence to the smart phone (step S9). Due to this, the smart phone <NUM> acquires the data representing cadence and displays the data on the display. The user can know the cadence by seeing the display of the smart phone <NUM>.

The main control unit <NUM> decides whether to terminate the processing (step S10). The time to terminate the processing is when a manipulation to terminate measurement processing by the cadence measurement device <NUM> is performed. If the main control unit <NUM> decides that the processing is not to be terminated (S10: NO), the main control unit <NUM> returns the flow to step S1. Also, if the main control unit <NUM> decides that the processing is to be terminated (S10: YES), the main control unit <NUM> terminates a series of processing.

As described above, the cadence measurement device <NUM> obtains a myoelectric potential waveform by performing filter processing on an output signal representing the myoelectric potential detected by the myoelectric potential sensor <NUM> and performing waveform processing such as processing to convert to root mean square values, and derives cadence from cycles included in the myoelectric potential waveform. In this case, there is no need to use a rotational speed sensor and there is also no need to use an acceleration sensor and the like, as in the past. Due to this, the cadence measurement device <NUM> can be realized with a very simple structure.

Therefore, it is possible to provide the cadence measurement device <NUM> having a simple structure and the cadence measurement method. Since the cadence measurement device <NUM> can be realized only with the myoelectric potential sensor <NUM>, MCU <NUM>, communication unit <NUM>, and battery <NUM>, the cadence measurement device <NUM> is very small and lightweight. Due to this, even when the user sticks the cadence measurement device <NUM> to the thigh with a tape or the like, the cadence measurement device <NUM> is less likely to drop off and cadence measurement can be stably continued for a long period of time. Also, even when the cadence measurement device <NUM> is stuck to the thigh of the user, there is very little feeling of discomfort, so the cadence measurement device <NUM> is superior in ease of attachment.

Also, in processing performed by an application program in the smart phone <NUM> after the myoelectric potential waveform measured by the cadence measurement device <NUM> is transmitted to the smart phone <NUM>, the degree of fatigue of muscles of the user and the like may be inferred and may be displayed on the display together with cadence. Then, the user can quantitatively grasp the degree of fatigue of muscles of the user together with the cadence.

Incidentally, an aspect has been described above in which the cadence deriving unit <NUM> measures the period of each cycle included in the period T and derives the cadence for which the period of one cycle is closest to each of periods T1 to T3. However, table data that relates cadence and the number of revolutions of the crank per second to each other may have been stored in the memory <NUM> instead of the table data indicated in <FIG>. Then, in the table data, the cadence closest to the reciprocal (number of revolutions of the crank per second) of the period of each cycle may be derived, the reciprocal being obtained by performing a Fourier transform on the myoelectric potential waveform indicated in <FIG>.

So far, the cadence measurement device and cadence measurement method in exemplary embodiments in the present invention have been described. However, the present invention is not limited to specifically disclosed embodiments. Various variations and modifications are possible without departing from the scope of the claims.

Claim 1:
A cadence measurement device (<NUM>), comprising:
a myoelectric potential sensor (<NUM>) adapted to be attached to a leg portion of a living body;
a waveform processing unit (<NUM>) configured to perform waveform processing to obtain a myoelectric potential waveform from an output signal of the myoelectric potential sensor; and
a cadence deriving unit (<NUM>) configured to derive, when an average value of an amplitude in a plurality of cycles of the myoelectric potential waveform obtained by the waveform processing is taken as an amplitude center and the myoelectric potential waveform is divided into each cycle according to the amplitude center, the cadence according to a period of each cycle;
wherein, if the waveform processing unit (<NUM>) decides that <NUM> seconds or more of amplitude data items of a digital waveform signal, obtained by Analog to Digital converting the output signal, have been accumulated, the waveform processing unit (<NUM>) is configured to perform band-pass filter processing on the digital waveform signal, wherein the waveform processing unit (<NUM>) is configured to extract components at <NUM> or less from the myoelectric potential waveform, wherein the waveform processing unit (<NUM>) is configured to obtain the myoelectric potential waveform from the output signal by performing, as the waveform processing, processing to convert the output signal of the myoelectric potential sensor (<NUM>) to a signal waveform with a root mean square value, wherein the waveform processing unit (<NUM>) is configured to obtain the myoelectric potential waveform from the output signal by performing, as the waveform processing, processing to extract a component waveform, which is a waveform of a frequency component included in the myoelectric potential waveform of the living body, from the output signal of the myoelectric potential sensor (<NUM>) and processing to convert the component waveform to a signal waveform with a root mean square value,
wherein the cadence measurement device (<NUM>) is configured to perform waveform processing in the following order: S3 band-pass filter processing, S4 convert to waveform with root mean square values, S5 low-pass filter processing, S6 calculate average of amplitudes, S7 measure period of each cycle and S8 derive cadence.