WO2016096454A1

WO2016096454A1 - Method for determining activity characteristics

Info

Publication number: WO2016096454A1
Application number: PCT/EP2015/078495
Authority: WO
Inventors: Kresten Juel Nikolaj Laut Jensen; Mads Find Madsen
Original assignee: Mo2Tion Technology Innovation Aps
Priority date: 2014-12-16
Filing date: 2015-12-03
Publication date: 2016-06-23

Abstract

Disclosed is a method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, where one or more inertial sensors are attached on the first part of the equipment, the method comprising generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment, when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and determining the activity characteristic based on the time series.

Description

METHOD FOR DETERMINING ACTIVITY CHARACTERISTICS

FIELD

The present disclosure relates to a method for determining an activity characteristic of an activity. The activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part. More particularly, one or more inertial sensors are attached on the first part of the equipment.

BACKGROUND

US201 1040500A discloses a bicycle power meter which has a strain gauge sensor assembly mounted on a relatively compressible portion of the end of the rear fork of the bicycle frame. The relatively compressible portion is near the rear hub and subject to the forces exerted by the cyclist to the crankset, and transferred via the chain, and sprocket assembly to the hub. The sensor assembly has two ohmically interconnected stretch sensors each having a first layer bearing a variable resistance element, whose resistance changes with displacement of the compressible portion, and a second layer for providing support for the first layer. The sensor assembly is connected in a bridge circuit to two other resistances to generate signals representative of cyclist applied force. These signals are processed along with velocity signals to generate power signals and the power signals are supplied to a display

US201 1 1 18086 AA discloses a control system and method for exercise equipment and the like which provides a way to simulate a physical activity in a manner that takes into account the physics of the physical activity being simulated to provide an accurate simulation. According to one aspect of the disclosure, the control system and method takes into account the physics of the corresponding physical activity to generate a virtual or predicted value of a variable such as velocity, acceleration, force, or the like. The difference between the virtual or expected physical variable and a measured variable is used as a control input to control resistance forces of the exercise equipment in a way that causes the user to experience forces that are the same or similar to the forces that would be encountered if the user were actually performing the physical activity being simulated rather than using the exercise equipment. WO0130643A1 discloses that the level of a force or torque (T) exerted by a rider on the pedals (27) of a bicycle (1 ) is calculated by a signal-processing device (40) on the basis of a measurement signal which is obtained from a sensor (50) which is attached to the frame (10) of the bicycle in order to measure the deformation which occurs in the frame. The sensor (50) may comprise one or more strain gauges. Furthermore, the invention describes a way of actuating a hub motor (45) on the basis of the chain force. This arrangement always offers the considerable advantage that a single sensor (74; 50) is sufficient, and that this sensor can be mounted on the same bicycle component as that to which the control member (40) is attached, namely the rear axle (6) itself or the inner race (71 ) of the wheel bearing (7) which is fixed to the rear axle. A bending sensor (50) which is mounted on the rear axle measures the bending which occurs in the rear axle itself as a result of the pedalling force. A pressure sensor (74) which is mounted in the wheel bearing (7) measures the compressive forces caused in the wheel bearing by the chain force.

SUMMARY

There is a need for an improved method for determining activity characteristics of an activity performed on an equipment.

Disclosed is a method for determining an activity characteristic of an activity. The activity is performed by a user on an equipment. The equipment comprises a first part and a second part movable relative to the first part. The activity is performed by movement of the second part. One or more inertial sensors are attached on the first part of the equipment. The method comprises generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment, when the user performs the activity on the second part of the equipment. The inertial signal comprises a time series. The method comprises determining the activity characteristic based on the time series.

The method as disclosed provides an improved method for determining activity characteristics of an activity performed on an equipment as the direct movement or orientation of the equipment is not measured, instead the movement or orientation is determined by analysing the time series of the inertial sensors on the first part of device, which can be used to determine the activity characteristic of the movement performed by the user on the second part of the device.

Contrary to the present method, in prior art strain gauges are used in order to measure a deflection of deformation of the equipment.

It is an advantage that the present method does not measure the direct movement of the user or of the movable second parts of the equipment but uses the inertial sensors to measure movement or orientation of the first part of the equipment which is derived from or caused by the user performing movement of the movable second parts of the equipment.

The activity may be a sports activity, such as biking, spinning, rowing, performing fitness in a fitness machine etc. The equipment may be a bike, such as an indoor bike, a turbo trainer, a spinning bike, an outdoor bike, a bicycle, a mountain bike etc. The equipment may be a boat, such as a canoe, kayak, rowing boat etc. The equipment may be a fitness machine, such as rowing machine, a weight lifting machine etc. The activity may be performed in a fitness centre. The activity may be performed outside on a road, in water etc.

The first part of the equipment may be a frame of the equipment, such as handlebars of a bike and/or a front part of bike frame and/or a centre part of bike frame. The first part may be a frame of a rowing boat. The first part is configured to be rigid, steady, stationary and/or fixed when the user performs the activity on the equipment.

The second part of the equipment is movable relative to the first part. The activity is performed by movement of the second part, for example by movement of the second part relative to the first part, when the user performs the activity. The second part may be pedals on a bike and/or wheels on a bike. The second part may be a bicycle chain and/or a toothed wheel and/or a bottom bracket on a bike. The second part may be oars, sculls, paddles and/or sweeps of a boat, such as of a rowing boat, kayak and/or canoe. The second part may be the handlebars of a rowing machine functioning or taking the place of oars in a boat and/or the second part may be the seat of a rowing machine configured to move forwards and backwards on a horizontal track or bar of a rowing machine. The activity characteristic may for example be cadence, which is repetitions per time unit, and may be determined for example when the user is biking on a bike, such as bicycle, a spinning bike, a bike in a fitness center etc.

The one or more inertial sensors which are attached on the first part of the equipment may be a gyroscope and/or an accelerometer. The inertial sensor, e.g. the gyroscope and/or the accelerometer, may be attached on the handlebars of a bike. The inertial sensors, such as the gyroscope and/or the accelerometer, may be implemented or mounted in a communication device, such as in a smart phone or mobile phone. Thus the inertial sensors may be the gyroscope and/or accelerometer present in a mobile phone, such as the gyroscope and/or accelerometer integrated by default in a mobile phone.

Thus, it is an advantage that no special or extra hardware devices may be required in order to perform the method, as inertial sensor(s), already integrated in a mobile phone per default, may be used to perform the method. The method comprises generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment, when the user performs the activity on the second part of the equipment. Thus it is an advantage that no sensor is needed on the second part of the equipment in order to perform the method. Only inertial sensor(s) on the first part of the equipment is used without a need for sensors on the second part of the equipment.

The inertial signal comprises a time series and/or a plurality of time series. The time series may be time series of measurements of the one or more inertial sensors. The time series may be a time signal. The time series may be a time domain

representation. The time series may be a time interval, such as a predefined time interval. The predefined time interval may be such as five seconds, 10 seconds, 15 seconds, 20 seconds, 30 seconds, 40 seconds, 50 second, 60 seconds, 70 seconds, 80 seconds, 90 seconds, 100 seconds etc. The predefined time interval may be such as one minute, two minutes, three minutes, four minutes, five minutes, six minutes, seven minutes, eight minutes nine minutes, ten minutes, 20 minutes, 30 minutes, 40 minutes, 50 minutes, 60 minutes etc. The time series may comprise a number of data sets, such as a predefined number of data sets, such as five data sets, 10 data sets, 20 data sets, 30 data sets, 40 data sets, 50 data sets, 60 data sets etc. Also disclosed is a communications device configured to perform a method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, wherein the communications device comprises one or more inertial sensors, and wherein the communications device is configured to be mounted to the first part of the equipment, the method comprising generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and determining the activity characteristic based on the time series, and wherein the communications device is configured to display the determined activity characteristic on a display of the communication device.

Also disclosed is system comprising a communications device and an equipment, the system is configured to perform method for determining an activity characteristic of an activity, where the activity is performed by a user on the equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, wherein the communications device comprises one or more inertial sensors, and wherein the communications device is configured to be mounted to the first part of the equipment, the method comprising generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and determining the activity characteristic based on the time series, and wherein the communications device is configured to display the determined activity characteristic on a display of the communication device.

Also disclosed is a computer program application configured to run on a

communications device, where the computer program application is configured to perform a method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, wherein the communications device comprises one or more inertial sensors, and wherein the communications device is configured to be mounted to the first part of the equipment, the method comprising generating by and/or receiving from the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and determining the activity characteristic based on the time series, wherein the computer program application is configured to display the determined activity characteristic on a display of the communications device.

Also disclosed is a server configured to perform a method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, where one or more inertial sensors are mounted/attached on the first part of the equipment, the method comprising generating by and/or receiving from the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and determining the activity characteristic based on the time series, wherein the server is configured to transmit the determined activity characteristic to a computer program application run on a communications device and configured to display the determined activity characteristic on a display of the communications device.

In some embodiments determining the activity characteristic comprises determining a periodicity of the time series, and wherein the activity characteristic is based on the periodicity of the time series.

In some embodiments determining the activity characteristic comprises determining force and/or acceleration and/or deceleration and/or power and/or impulse and/or momentum and/or work and/or duration of phases and/or stability and/or asymmetries.

Duration of phases and/or stability and/or asymmetries may be determined for force and/or acceleration and/or deceleration and/or power and/or impulse and/or momentum and/or work. Duration of phases and/or stability and/or asymmetries and/or force and/or acceleration and/or deceleration and/or power and/or impulse and/or momentum and/or work may be determined by assigning subsets of the time series to sub-activities. The sub- activities may be such as using the left or right body part, such as the left or right leg when biking. The sub-activities may be strokes or steps. The sub-activities may be using force and using no force. Determining the sub-activities may be based on amplitude and/or direction of the inertial signals, such as selected inertial signals. Determining the duration of phases and/or stability and/or asymmetries and/or force and/or acceleration and/or deceleration and/or power and/or impulse and/or momentum and/or work may comprise comparing variance and/or amplitude and/or integrated signal of the individual subsets, such as left vs. right subsets of force time. Force time may be the time interval in which force by the user is applied to the second movable part of the equipment.

Acceleration and/or deceleration and/or power and/or impulse and/or momentum and/or work and/or duration of phases and/or stability and/or asymmetries may be determined by evaluating variance and/or amplitude and/or integrated signal of the full data set, i.e. no subsets, for a selected part of the time series.

In some embodiments determining the activity characteristic comprises generating a frequency spectrum based on the time series.

The frequency spectrum may be a frequency signal, a function of frequency, a frequency domain representation.

In some embodiments determining the activity characteristic comprises analysing the frequency spectrum to determine peak frequencies. The activity characteristic may be based on the peak frequencies.

In some embodiments determining the activity characteristic comprises analysing the frequency spectrum to determine a maximum frequency in a specified frequency range of the frequency spectrum. The activity characteristic may be based on the maximum frequency in the specified frequency range. The specified frequency range may be for example 0.25 Hz to 5 Hz, such as 1 Hz to 2 Hz.

In some embodiments the time series is Fourier transformed to generate the frequency spectrum. The Fourier transformation may be a Fast Fourier Transform.

In some embodiments the inertial signal comprises measurements of movements in one or more axes/directions of the inertial sensor.

Thus the inertial sensor may be a multi-axis inertial sensor, such as an inertial sensor measuring in both a x-direction, and/or a y-direction and/or a z-direction. Thus it is movements of the first part of the equipment which is measured by the inertial sensor.

In some embodiments the measurements of movements in one or more of the axes/directions of the one or more inertial sensors are selected for determining the activity characteristic.

In some embodiments the one or more inertial sensors comprises a plurality of different types/kinds of sensors.

In some embodiments the one or more inertial sensors comprises an accelerometer and/or a gyroscope.

The inertial sensors may alternatively and/or additionally comprise a compass, an altimeter or an altitude meter, an inertial measurement unit (IMU) etc.

In some embodiments the accelerometer and/or gyroscope is single-axis or multi-axis.

Thus the accelerometer and/or gyroscope may measure in one axis, two axes, or three axes. In some embodiments the activity characteristic is determined based on phase shifts between one or more frequency signals of the frequency spectrum.

One frequency signal may be generated from each sensor. One frequency signal may be generated from each axis of each sensor. Thus one or more frequency signals may be generated.

In some embodiments the activity characteristic is determined based on phase differences between one or more frequency signals of the frequency spectrum.

In some embodiments the activity characteristic is a cadence (revolutions/time), and where the equipment is a bike/cycle.

The second part of the equipment may then be a pedal and the first part of the equipment may then be the frame or handlebars of the bike.

In some embodiments the one or more inertial sensors is arranged in a

communications device, and where the communications device is configured to be attached on the first part of the equipment.

The communications device may be a smart phone, a mobile phone, a tablet, a pc, a watch, such as a smart watch, an activity tracker etc.

In some embodiments the one or more inertial sensors and/or the communications device is configured to be arranged in any orientation on the first part of the equipment.

Thus the inertial sensors can be arranged in any orientation and thus the activity characteristic can be determined no matter how the orientation of the inertial sensor is. In some embodiments the time series is obtained within a time interval adapted for the specific activity performed by the user.

For example for biking, the time interval may be shorter than for rowing, as biking is typically performed with a higher cadence than rowing.

In some embodiments the time series is obtained within a time interval adapted for the specific one or more inertial sensors and/or the specific communications device in which the one or more inertial sensors is arranged. Thus for a high-end inertial sensor, such as arranged in a high-end communications device, the time interval may be shorter than for a low-end inertial sensor.

In some embodiments the time series from the one or more inertial sensors is obtained within a time interval of less than 60 seconds. The time interval may be less than 50 seconds, or less than 40 seconds, or less than 30 seconds, or less than 20 seconds, or less than 10 second. The time interval may be more than 60 seconds, such as more than 70 second, more than 80 seconds, more than 90 seconds etc.

In some embodiments the communications device comprises a computer program application configured to communicate with a server, and wherein the method comprises transmitting the inertial signal by the computer program application to the server, determining the activity characteristic by the server, transmitting the determined activity characteristic by the server to the computer program application, and displaying/presenting the determined activity characteristic to the user in the computer program application on the communications device.

The transmitted inertial signal may be the whole inertial signal or selected data from the inertial signal, such as pre-processed data, e.g. in order to save power for the processing and/or limit transmission of data. The server may be a stationary server, or a cloud-based server etc. The displaying or presenting of the determined activity characteristic may be in the computer program application, such as in an app on a smart phone or tablet, such as on a display, such as as visual information, such as as audible information etc.

The present invention relates to different aspects including the method described above and in the following, and corresponding systems, methods, devices, systems, networks, kits, uses and/or product means, each yielding one or more of the benefits and advantages described in connection with the first mentioned aspect, and each having one or more embodiments corresponding to the embodiments described in connection with the first mentioned aspect and/or disclosed in the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features and advantages will become readily apparent to those skilled in the art by the following detailed description of exemplary embodiments thereof with reference to the attached drawings, in which:

FIG 1 shows exemplary inertial sensor placements on a bike.

FIG 2 shows exemplary local axis accelerometer values for 25 seconds of a bike ride.

FIG 3 shows an example of the normalized Fourier components as a function of cadence (or similarly frequency).

FIG 4 shows an example of the computed bike cadence values for 43 30sec intervals.

FIG 5 illustrates an exemplary flow chart of the method for determining an activity characteristic of an activity.

DETAILED DESCRIPTION

Various embodiments are described hereinafter with reference to the figures. Like reference numerals refer to like elements throughout. Like elements will, thus, not be described in detail with respect to the description of each figure. It should also be noted that the figures are only intended to facilitate the description of the embodiments. They are not intended as an exhaustive description of the claimed invention or as a limitation on the scope of the claimed invention. In addition, an illustrated embodiment needs not have all the aspects or advantages shown. An aspect or an advantage described in conjunction with a particular embodiment is not necessarily limited to that embodiment and can be practiced in any other embodiments even if not so illustrated, or if not so explicitly described.

Throughout, the same reference numerals are used for identical or corresponding parts.

Exercise, rehabilitation, and other activities are often conducted on equipment like bikes, kayaks, step machines, rowing machines, weight lifting machines etc. The equipment typically comprises both a frame and moving parts such as pedals, drivechain(s), wheels, oars.

The transfer of energy from user to equipment occurs through the moving parts. The characteristics of this transfer are often of interest to the user. One example is the cadence, i.e. the number of revolutions/steps/events per minute. Prior art uses inertial sensors attached either to the user or the moving parts of the equipment to

characterize the transfer of energy and movement of the user. This can be

cumbersome, instable, and annoying to the user.

The present disclosure discloses a method to produce energy transfer and movement characteristics information characterized in the use of inertial measurements recorded by sensors attached to the frame of the equipment instead of the moving parts or the user.

Several activities within sports, rehabilitation, exercise etc. use equipment such as bikes, boats, fitness machines, weight lifting machines etc.

This equipment consists of both a frame and moveable parts taking part in the energy transfer from user to equipment, also named the drive chain. Examples of movable parts are pedals, wheels, chains, and oars. In this context the frame of the equipment is any part, which is not an active part of the energy transfer. Examples are the frame, the handlebars, and the saddle of a bike or the hull of a boat. Similarly most fitness and weight lifting machines have a frame stabilising the equipment and movable parts for the user to perform work on.

For all of these types of equipment and activities it can be relevant for the user, coach, or health professional to measure the characteristics of the performed activity in order to optimise or track the activity performance. Examples are cadence, which on a bike is revolutions per time unit, asymmetry of energy transfer between left and right side, stability of the user's body on the equipment, and the interaction forces between user and equipment.

Prior art cycle- and fitness computers displaying the characteristics of the user activity are in some cases based on inertial sensors attached to either the user as described in WO2014109982 (A2) or as done in foot pods, which are accelerometers placed on the runner's foot. These systems count events (acceleration values above a certain threshold) or find the cadence of an activity by Fourier analysis of the inertial sensor signal finding the maximum amplitude frequency.

Another example of equipment based activity characterisation is the measurement of cycling cadence using a cyclocomputer which is a sensor system including magnets mounted to both the crank arm of the bicycle and the bike frame counts the number of rotations per minute to determine the cycling cadence. While such devices are useful and reasonably accurate, they are cumbersome and cannot easily be used for an accurate estimate of cadence on equipment designed for other activities, such as fitness machines.

Bike power-meters are mounted inside the crank box or in the pedals to calculate the power transferred from the user to the bike moving parts.

The present method solves the problem of mounting the inertial sensors to either a user (person) or the moveable parts of the equipment. Two main problems exist:

1 . The risk of sensor displacement is higher, when the surface on which it is mounted is moving. This can make the device malfunction or fall off.

2. Collecting display and sensor in one device is difficult, as a moving display is harder to watch, and it cannot necessarily be placed in a visible position to the user.

The present method solves the problems above by the following method:

Recording the signals from inertial sensor(s) mounted on the equipment frame, e.g. frame including handlebars, saddle, etc. of a bike, and processing the recorded signals to obtain activity characteristics.

It is a surprising effect that the activity characteristics, such as cadence, can be derived from the inertial signals measured on the frame which is the part of the equipment, which is designed to be fixed/steady/stiff, such as the frame or handlebars of a bike. This example is shown in FIG 1 . This method is not obvious, as the amplitude of the noise (vibrations) often is much larger than the amplitude of the periodic signal of interest as shown in FIG 2 having no visible periodic signal - only noise. Typically it requires Fast Fourier Transform (FFT) analysis, signal smoothing, or similar data analysis to even detect the part of the signal, which is relevant user activity

characteristics, e.g., cadence. In case of multiple sensors or axes of measurement it is an advantage to use a selection algorithm for choosing or combining a signal containing the largest periodic signal relevant for analysis.

In prior art using inertial signals to extract activity characteristics such as cadence from sensors mounted on the user or the moving parts of the equipment, the periodic signal of interest is clearly dominating the noise, making it easily implementable in a processor and therefore the current state-of-the-art. E.g., the circular pedal movement on a bike provides a much stronger signal than that of the vibrations from the road.

FIG 1 shows two possible inertial sensor placements on a bike following the present method where "A": On the handlebars of the bike. "B": On the bike frame.

FIG 2 shows local axis accelerometer values for 25 seconds of a bike ride without any obvious periodic signal. The accelerometer was mounted on the handlebars and sampling at 40 Hz. The used accelerometer was that of a mobile phone with a range of 20 m/s^A2.

FIG 3 shows the normalized Fourier components as a function of cadence (or similarly frequency) revealing a maximum at 72 revolutions/minute corresponding to the visual count. The analysis is based on the signal presented in FIG 2.

FIG 4 shows the computed bike cadence values for 43 30sec intervals utilizing the described method including selective FFT analysis. The cadences correspond well to visual count. 5 outliers have been marked, as these represent the times when the bike is at full stop.

The present method utilizes inertial sensors to measure and isolate typically very weak periodic signals from the frame of activity equipment and thereby extracting relevant information about the activity performed on/with the equipment. In other words the method comprises of the following steps: Recording the signals from inertial sensor(s) mounted on the equipment frame, and processing the recorded signals for activity characteristics. Examples of the latter step, processing, is given in the following. Compared to prior art this method has the advantage of utilising measurements with low signal/noise ratios along with the advantages of being able to combine display and sensor(s) in the same housing in a fixed, non-moving position and minimizing the risk of malfunction due to displacement from a moving part.

Typical areas of use are outdoor and indoor bikes, rowing machines, rowing boats, kayaks, weight lifting machines, stepping machines, running treadmills, crosstrainers, elliptical trainers, and other fitness/training/exercise/rehabilitation equipment/machines.

The present method prescribes a mounting position on the frame of such equipment. By frame is meant the parts of the equipment not being a part of the drive chain and thereby not designed to have a periodic movement during activity. On a bike it can be the handlebars or frame, as shown in FIG 1 , which are excellent positions for a cyclocomputer containing both sensor and display. On boats and kayaks the hull or seat is considered part of the frame. On fitness machines, like treadmills, crosstrainers, elliptical trainers, stepping machines, rowing machines etc. there is often a display mounted on the frame stabilizing the equipment. In or close to this display is also a relevant position for the inertial sensor mounting according to the present method. Many other frame positions are available on such equipment.

Inertial sensors include but is not limited to accelerometers (single and multi-axis) and gyroscopes (single and multi-axis). Other sensors and equipment provide similar information about the frame inertials and are in this context contained in the group of inertial sensors, including laser and optics detectors, cameras, strain gauge, barometers, etc. of which many are present in mobile phones, activity trackers and other wearable devices.

All equipment and activities have their own relevant characteristics depending also on the user, coach, practitioner, or other end user. Relevant characteristics examples are: Cadence (repetitions per time unit) - also known as frequency -, force, acceleration, deceleration, power, duration of specific phases, stability (movement amplitude), etc. Differences between right and left side components, i.e., asymmetries, are also relevant.

In the present method the inertial signals from periodic activity is processed to obtain such information. Any method filtering out the noise from the relevant information about the periodic signal related to the activity, or methods extracting information directly, can be used including Fourier analysis, Principal Component Analysis (PCA), Signal smoothing, Threshold Evaluation, etc. Having more than one inertial signal it can be beneficial to do a pre-evaluation of the signals to base the analysis on the most relevant axis, or the one with the periodic signal having the largest amplitude. Isolated periodic signals from several sources can also be combined to provide a stronger signal for calculating the activity characteristics. The above mentioned analysis methods are useful in this context as well.

One of the most requested activity characteristics is the cadence (revolutions/minute) of a bike ride. The present method solves this request.

In an exemplary method, data is recorded from a 3-axis accelerometer of a mobile phone mounted on the handlebars of a bike (shown as mount position A in FIG 1 ). This mount is often used for mobile phones running apps showing key information about the ride. Using data from a phone accelerometer mounted in this way is therefore beneficial to the user as it excludes additional sensors on the pedals, wheels or other parts of the drive chain as known from prior art. The recording frequency in this example is approximately 40Hz and data from one of the axes is shown for a 25 second interval in FIG 2. Data from all three axes undergo Fourier analysis, and the maximum power frequency in the specified range (here 1 -2Hz) is found. Comparison of the power values for all three axes is used as selection criteria for the axis providing the best signal for cadence evaluation (revolutions/minute). The result of the Fourier analysis for a 30 second interval is shown in FIG 3 finding the cadence to be 72 revolutions/minute. For a full bike ride of 22 minutes the method is applied for all 30 second intervals finding the cadence for all times as shown in FIG 4. This analysis can run in real time. Five outliers are marked showing the times at which the bike was not moving. Such values can be eliminated by comparing the general acceleration values with a threshold value indicating, if the bike is moving or parked.

Finding the periodicity of the signal, further activity characteristics can be produced:

Integrating the periodic accelerations yields the: 1 . left/right oscillation of the bike, 2. forward accelerations and decelerations for left and right leg work phases, and 3. the power output of each leg can be estimated on the basis hereof.

Left/right axis oscillations can also be used to extract the time standing and sitting in the saddle comparing to threshold values separating the two activities.

The road quality is another possible output from this method when the user induced oscillations are extracted as periodic signals. The remaining noise may be a measure of road quality, which is both an activity characteristic important to the rider and an input for speed compensation calculations. Saving this road quality value paired with the location makes this information available to others riding on the same road or planning to do so, making it a useful input for route planning. Similar approach for other activity characteristics can be used to inform others of typical values at specific locations to evaluate the best route for a specific purpose. This also applies during the ride in a live version.

The exemplary method enables both known and new output to the rider compared to prior art, but has a practical technical advantage compared to prior art, as the sensors are mounted on the frame (including handlebars) instead of on moving parts (pedals, wheels, crank, chain).

Fig. 5 illustrates an exemplary flow chart of the method for determining an activity characteristic of an activity. The activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part. One or more inertial sensors are attached on the first part of the equipment. The method comprises:

In step 101 an inertial signal indicative of movement of the first part of the equipment is generated, by the one or more inertial sensors, when the user performs the activity on the second part of the equipment. The inertial signal comprising a time series. In step 102 the activity characteristic is determined based on the time series.

Although particular features have been shown and described, it will be understood that they are not intended to limit the claimed invention, and it will be made obvious to those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the claimed invention. The specification and drawings are, accordingly to be regarded in an illustrative rather than restrictive sense. The claimed invention is intended to cover all alternatives, modifications and equivalents.

ITEMS

1 . A method for determining an activity characteristic of an activity involving equipment with a frame from an inertial signal generated by an inertial sensor characterized in that the inertial signal is collected from an inertial sensor mounted on the frame of the 5 equipment.

2. The method of item 1 wherein the equipment is a bicycle.

3. The method of item 1 wherein the equipment is a fitness machine.

4. The method of item 1 wherein the equipment is a sailing vehicle.

5. The method of item 1 wherein the equipment is treadmill. 10

6. The method of items 1 -5 wherein the determined activity characteristic is the cadence determined by determining the peak frequency of the signal and defining an activity specific frequency interval in which the peak frequency is searched for.

7. The method of items 1 -6 wherein multiple sensor signals are processed and the periodic signal strength for the sensors are compared before determining the activity characteristic on the basis of the signal having the strongest periodic signal.

8. The method of items 1 -7 wherein multiple sensor signals are combined before determining the activity characteristic.

9. The method of items 1 -8 wherein an activity characteristic is derived from integration of one or more sensor signals or isolated periodic parts of the signal. 20

10. The method of items 1 -9 wherein the derived activity characteristic is related to a specific location and the activity characteristic value and location pairs are stored.

Claims

1 . A method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, where one or more inertial sensors are attached on the first part of the equipment, the method comprising: generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment, when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and determining the activity characteristic based on the time series.

2. Method according to any of the preceding claims, wherein determining the activity characteristic comprises determining a periodicity of the time series, and wherein the activity characteristic is based on the periodicity of the time series.

3. Method according to any of the preceding claims, wherein determining the activity characteristic comprises determining force and/or acceleration and/or deceleration and/or impulse and/or momentum and/or work and/or power and/or duration of phases and/or stability and/or asymmetries.

4. Method according to any of the preceding claims, wherein determining the activity characteristic comprises generating a frequency spectrum based on the time series.

5. Method according to claim 4, wherein determining the activity characteristic comprises analysing the frequency spectrum to determine peak frequencies, and wherein the activity characteristic is based on the peak frequencies.

6. Method according to any of claims 4-5, wherein determining the activity

characteristic comprises analysing the frequency spectrum to determine a maximum frequency in a specified frequency range of the frequency spectrum, and wherein the activity characteristic is based on the maximum frequency in the specified frequency range.

7. Method according to any of claims 4-6, wherein the time series is Fourier transformed to generate the frequency spectrum.

8. Method according to any of the preceding claims, wherein the inertial signal comprises measurements of movements in one or more axes/directions of the inertial sensor.

9. Method according to the preceding claim, wherein the measurements of movements in one or more of the axes/directions of the one or more inertial sensors are selected for determining the activity characteristic.

10. Method according to any of the preceding claims, wherein the one or more inertial sensors comprises a plurality of different types/kinds of sensors.

1 1 . Method according to any of the preceding claims, wherein the one or more inertial sensors comprises an accelerometer and/or a gyroscope.

12. Method according to the preceding claim, wherein the accelerometer and/or gyroscope is single-axis or multi-axis.

13. Method according to any of the preceding claims, wherein the activity characteristic is determined based on phase shifts between one or more frequency signals of the frequency spectrum.

14. Method according to any of the preceding claims, wherein the activity characteristic is determined based on phase differences between one or more frequency signals of the frequency spectrum.

15. Method according to any of the preceding claims, wherein the activity characteristic is a cadence (revolutions/time), and where the equipment is a bike/cycle.

16. Method according to any of the preceding claims, wherein the one or more inertial sensors is arranged in a communications device, and where the communications device is configured to be attached on the first part of the equipment.

17. Method according to any of the preceding claims, wherein the one or more inertial sensors and/or the communications device is configured to be arranged in any orientation on the first part of the equipment.

18. Method according to any of the preceding claims, wherein the time series is obtained within a time interval adapted for the specific activity performed by the user.

19. Method according to any of the preceding claims, wherein the time series is obtained within a time interval adapted for the specific one or more inertial sensors and/or the specific communications device in which the one or more inertial sensors is arranged.

20. Method according to any of the preceding claims, wherein the time series from the one or more inertial sensors is obtained within a time interval of less than 60 seconds.

21 . Method according to any of the preceding claims, wherein the communications device comprises a computer program application configured to communicate with a server, and wherein the method comprises: - transmitting the inertial signal by the computer program application to the server,

- determining the activity characteristic by the server,

- transmitting the determined activity characteristic by the server to the computer program application, and

- displaying/presenting the determined activity characteristic to the user in the computer program application on the communications device.

22. A communications device configured to perform a method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, wherein the communications device comprises one or more inertial sensors, and wherein the communications device is configured to be mounted to the first part of the equipment, the method comprising:

- generating, by the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and - determining the activity characteristic based on the time series, and wherein the communications device is configured to display the determined activity characteristic on a display of the communication device.

23. A system comprising a communications device and an equipment, the system is configured to perform method for determining an activity characteristic of an activity, where the activity is performed by a user on the equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, wherein the communications device comprises one or more inertial sensors, and wherein the communications device is configured to be mounted to the first part of the equipment, the method comprising:

24. A computer program application configured to run on a communications device, where the computer program application is configured to perform a method for determining an activity characteristic of an activity , where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, wherein the communications device comprises one or more inertial sensors, and wherein the communications device is configured to be mounted to the first part of the equipment. the method comprising: - receiving, from the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and - determining the activity characteristic based on the time series, wherein the computer program application is configured to display the determined activity characteristic on a display of the communications device.

25. A server configured to perform a method for determining an activity characteristic of an activity, where the activity is performed by a user on an equipment, where the equipment comprises a first part and a second part movable relative to the first part, where the activity is performed by movement of the second part, where one or more inertial sensors are mounted/attached on the first part of the equipment, the method comprising:

- receiving from the one or more inertial sensors, an inertial signal indicative of movement of the first part of the equipment when the user performs the activity on the second part of the equipment, the inertial signal comprising a time series, and

- determining the activity characteristic based on the time series, wherein the server is configured to transmit the determined activity characteristic to a computer program application run on a communications device and configured to display the determined activity characteristic on a display of the communications device.