A multi-functional exercise bicycle system

Abstract

The present application relates to the technical field of resistance adjustment, in particular to a multifunctional exercise bike system, which comprises a pedal frequency identification module, a state determination module, a stage control module, a load adjustment module and an output response module.In the present application, through continuous analysis of pedal frequency and time information, the rhythm fluctuation state is accurately identified, the dynamic judgment of movement stability is realized by combining the linkage change of flywheel speed and pedal pressure, the matching mechanism of training time and stage setting is combined, the accuracy and continuity of training stage switching are improved by combining pedal frequency deviation and flywheel state change, the resistance adjustment strategy is derived according to the relationship between flywheel acceleration and pedal pressure, the sensitivity and precision of control response are enhanced, the load weight is set by fusing the heart rate change trend, the resistance output is more suitable for individual physiological state, the load rhythm matching degree is optimized, and the overall rhythm following ability, resistance adjustment rationality and training individualization level are improved.

Description

Technical Field

[0001] This invention relates to the field of resistance adjustment technology, and in particular to a multifunctional exercise bike system. Background Technology

[0002] The field of resistance adjustment technology for indoor cycling involves methods and structures for adjusting resistance in fitness training equipment to simulate resistance changes caused by different road conditions during actual cycling. Its core aspects include applying varying degrees of exercise load to users through mechanical structures, electrical controls, or pneumatic-hydraulic systems to meet diverse training needs such as aerobic training, strength training, or rehabilitation therapy. This technology constructs a complete training system by building pedals, a flywheel, and connected braking and adjustment components, and combines this with control strategies to achieve dynamic resistance management. Traditional multi-functional indoor cycling systems refer to indoor fitness equipment that integrates multiple exercise modes or additional functions in addition to basic cycling training functions to enhance the training experience. The key technical issue addressed by such equipment is how to achieve multiple exercise combinations and resistance change control within a single device. Traditional multi-functional indoor cycling systems use mechanical friction plates, magnetic control, and electromagnetic control devices to adjust the resistance of the flywheel to cope with different cycling intensities and personalized training needs.

[0003] Existing technologies using mechanical friction plates, magnetic control, or electromagnetic control to adjust flywheel resistance, while achieving resistance changes, lack a real-time recognition mechanism for rhythm changes during training. They often rely on manual user adjustments or preset programs, failing to dynamically respond to actual exercise conditions. Due to the lack of comprehensive analysis of cadence trends, flywheel status, and pedal pressure, existing systems struggle to respond promptly to decreased user output or imbalanced training rhythm, easily causing training rhythm disruptions or overload incompatibility, thus reducing training effectiveness. Training phases rely on fixed-time switching or manual judgment, lacking intelligent judgment logic based on user status, potentially leading to uncontrolled phase transitions and affecting the systematic implementation of the training plan. Resistance control methods are mostly one-dimensional adjustments, failing to fully incorporate coupling logic with flywheel dynamic parameters, and the response strategy lacks fine-grained modeling, easily causing sluggish or unstable resistance adjustments. Furthermore, existing systems fail to incorporate physiological data such as heart rate changes for load response optimization during load adjustment, failing to dynamically adapt to individual differences, resulting in uneven training loads among different users, affecting training accuracy and safety. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a multifunctional exercise bike system. The technical solution is as follows:

[0005] On the one hand, a multifunctional exercise bike system is provided, which includes:

[0006] The cadence recognition module acquires cadence values ​​and time information during the training process, analyzes the cadence rate trend within a continuous time period, identifies the rhythm state based on the direction and amplitude of change, and generates rhythm fluctuation state labels.

[0007] The status determination module calls the rhythm fluctuation status label, combines the difference between the current and average flywheel speed, and refers to the change between the current and recent average pedal pressure to determine whether there is a power reduction and output pullback, and generates a stability determination signal.

[0008] The stage control module calls the stability judgment signal to obtain the current training time, matches it with the stage set time, compares the deviation of the current average pedal frequency from the previous stage, and when the conditions are met, generates a stage switching control command by combining the flywheel speed and pedal pressure.

[0009] The load adjustment module calls the stage switching control command to obtain the current resistance output level and analyze the difference. Referring to the relationship between flywheel acceleration and pedal pressure, it derives the control loading strategy and generates a resistance adjustment strategy template.

[0010] The output response module calls the resistance adjustment strategy template, combines the heart rate change trend to establish load response weights, and generates a resistance response rhythm mode based on the flywheel state and control delay.

[0011] As a further embodiment of the present invention, the rhythm fluctuation status label includes the cadence change direction, cadence change amplitude, and cadence change rate trend; the stability judgment signal includes the power change status, output pullback status, and rhythm stability level; the stage switching control command includes the stage switching basis, stage switching time point, and switching validity indicator; the resistance adjustment strategy template includes resistance output difference, flywheel acceleration correlation, and electronic control loading strategy; and the resistance response rhythm mode includes load response weight, flywheel state change, and control delay index.

[0012] As a further aspect of the present invention, the cadence recognition module includes:

[0013] The cadence extraction submodule extracts cadence values ​​and time points within a time period based on the cadence signal and corresponding time information during the training process, calls up cadence change and time change information between consecutive time periods, calculates the cadence change rate, and obtains the cadence change rate value.

[0014] The trend recognition submodule constructs a sequence of change direction and change amplitude information for a continuous time period based on the cadence change rate value, compares the change direction in adjacent time periods to determine the continuity of change, and calculates the trend offset rate by combining the change range of the change amplitude with the difference of the current amplitude, and obtains the trend offset rate value.

[0015] The state determination submodule calls the trend offset rate value and change direction sequence information to jointly determine the direction and offset of the current time period. Based on the direction change threshold and offset rate threshold in the rhythm fluctuation determination standard, it determines the rhythm state type and obtains the rhythm fluctuation state label.

[0016] As a further aspect of the present invention, the state determination module includes:

[0017] The tag calling submodule extracts the fluctuation direction and intensity type corresponding to the current tag based on the rhythm fluctuation state tag, and determines whether the rhythm state is in a stage change range by combining the time axis sequence and tag continuity, and obtains the rhythm change range value.

[0018] The speed difference calculation submodule calls the rhythm variation interval value, extracts the change amplitude between the current flywheel speed and the average flywheel speed within the set time period based on the numerical difference between the current flywheel speed and the recent average pedal pressure, calculates the synchronous change rate between the current output index and the reference value, and obtains the output change rate value.

[0019] The stability judgment submodule identifies the direction and amplitude of output fluctuations based on the correspondence between the output change rate value and the rhythm state change range, determines whether there is an overlapping range between the power reduction signal and the output pullback signal, and establishes a stability judgment signal.

[0020] As a further aspect of the present invention, the stage control module includes:

[0021] The time matching submodule calls the stability determination signal to obtain the current training time value. Based on the interval membership relationship between the start and end values ​​of the stage-defined time interval and the current training time value, it determines whether the current time falls within a single specified stage range and generates a stage matching marker value.

[0022] The cadence offset submodule obtains the values ​​of the current cadence and the average cadence of the previous stage based on the stage matching mark value, calculates the difference between the two, and compares the difference with the set cadence offset threshold to obtain the cadence offset status value.

[0023] The stage switching submodule extracts the conformity relationship of the three values ​​in the stage change boundary range based on the combined state characteristics between the pedal frequency offset state value, the current flywheel speed value, and the pedal pressure signal value, determines whether the current stage meets the switching conditions, and obtains the stage switching control command.

[0024] As a further aspect of the present invention, the load adjustment module includes:

[0025] The resistance difference submodule calls the stage switching control command value to obtain the current resistance output level value, calculates the difference based on the difference between the two values, compares the difference with the set resistance change threshold for interval comparison, and generates a resistance deviation amplitude value.

[0026] The electronic control relationship submodule obtains the flywheel acceleration value and the pedal pressure signal value based on the resistance deviation amplitude value, calculates the numerical correlation coefficient between the flywheel acceleration value and the pedal pressure signal value within the same interval, and makes a joint judgment based on the correlation coefficient and the resistance deviation amplitude value to obtain the load response judgment value.

[0027] The strategy generation submodule matches the resistance output level coefficient corresponding to the differential electric control loading type based on the load response judgment value, extracts the combination sequence of resistance output level coefficients under the current stage, constructs a complete adjustment logic template, and generates a resistance adjustment strategy template.

[0028] As a further aspect of the present invention, the output response module includes:

[0029] The template calling submodule calls the content of the resistance adjustment strategy template, extracts the resistance adjustment level value and adjustment time node sequence under the current stage, filters the adjustment level and time node that match the current motion cycle state, constructs the resistance adjustment sequence within the cycle, and generates the resistance adjustment sequence value.

[0030] The weight establishment submodule obtains the heart rate change trend value based on the resistance adjustment sequence value, compares the growth rate of the heart rate change trend value in adjacent time periods with the set heart rate response benchmark rate, adjusts the adjustment intensity level of the corresponding segment in the resistance adjustment sequence value according to the difference amplitude, and establishes the load response weight coefficient.

[0031] The rhythm generation submodule collects flywheel state change values ​​and control delay index values ​​based on the load response weighting coefficient, calculates the ratio of flywheel state change values ​​and control delay index values ​​within the corresponding time period, and combines the ratio values ​​with the load response weighting coefficient to obtain the resistance response rhythm pattern.

[0032] As a further aspect of the present invention, the cadence value refers to the number of times a user's foot rotates on the pedals of a stationary bike per unit time, expressed in revolutions per minute, and is collected by a cadence sensor installed on the pedal axle or freewheel;

[0033] The rate trend refers to the time series trajectory formed by the direction and magnitude of the increase or decrease in cadence over multiple consecutive time periods.

[0034] The rhythm fluctuation status label refers to the classification result generated based on the trend change of cadence rate, which is used to identify whether the rhythm is stable, declining or fluctuating abnormally, and serves as one of the criteria for judging the training state.

[0035] As a further aspect of the present invention, the average flywheel speed refers to the arithmetic mean of the flywheel rotation speed within the target time period, in units of revolutions per minute or angular velocity, which is collected in real time by the flywheel sensing device.

[0036] The output pullback refers to the decrease in pedaling pressure applied by the user during cycling, reflecting a reduction in exercise intensity or signs of fatigue, and is supported by data provided by the pedal pressure sensor.

[0037] The stage setting time refers to the time threshold corresponding to each stage predefined by the system when setting up the training course;

[0038] The stage switching control command refers to the target resistance parameter calculated based on the current flywheel speed and pedal force level after the system verifies that the stage switching criteria have been met.

[0039] As a further aspect of the present invention, the flywheel acceleration refers to the rate of change of the flywheel angular velocity per unit time, which is obtained by differential analysis of continuous angular velocity data;

[0040] The electronically controlled loading strategy refers to a set of logical strategies generated based on the current resistance state, stage switching instructions, and user output to adjust the output mode of the electronically controlled resistance unit.

[0041] The resistance adjustment strategy template refers to the standardized control model derived by the system based on the current training state for controlling the resistance adjustment process.

[0042] The load response weight refers to the weighting parameter formed by combining the user's heart rate change trend;

[0043] The flywheel state refers to the trend of the flywheel's rotational speed change per unit time, which is manifested as acceleration, deceleration, or constant speed.

[0044] The control delay refers to the time delay between the issuance of a control command and the actual response of the electronically controlled resistance unit.

[0045] The resistance response rhythm pattern refers to the output rhythm type generated by factors such as training status, user heart rate, flywheel changes, and system response delay.

[0046] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0047] In this invention, by continuously analyzing cadence and time information, the rhythm fluctuation state is accurately identified. Combined with the linkage changes of flywheel speed and pedal pressure, dynamic judgment of exercise stability is achieved. The matching mechanism of training time and stage settings, combined with cadence deviation and flywheel state changes, improves the accuracy and continuity of training stage switching. The resistance adjustment strategy is derived based on the relationship between flywheel acceleration and pedal pressure, enhancing the sensitivity and accuracy of the control response. The load weight is set by integrating heart rate change trends, making the resistance output more in line with the individual's physiological state, optimizing the load rhythm matching degree, and improving the overall rhythm following ability, resistance adjustment rationality and training personalization level. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a system flowchart of the present invention;

[0050] Figure 2 This is a system block diagram of the present invention;

[0051] Figure 3 This is a flowchart of the cadence recognition module in this invention;

[0052] Figure 4 This is a flowchart of the state determination module in this invention;

[0053] Figure 5 This is a flowchart of the stage control module in this invention;

[0054] Figure 6 This is a flowchart of the load adjustment module in this invention;

[0055] Figure 7 This is a flowchart of the output response module in this invention. Detailed Implementation

[0056] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0057] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0058] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0059] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0060] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0061] This invention provides a multifunctional exercise bike system, such as... Figure 1-2 The diagram shows a multi-functional exercise bike system, which includes:

[0062] The cadence recognition module acquires cadence values ​​and time information during the training process, analyzes the rate trend of cadence change within a continuous time period, and identifies the current rhythm state based on the direction and magnitude of change within multiple consecutive time periods, generating rhythm fluctuation state labels.

[0063] The cadence value refers to the number of times a user's foot rotates on the pedals of a stationary bike per unit time, expressed in revolutions per minute (RPM), and is collected by a cadence sensor installed on the pedal axle or freewheel;

[0064] Rate trend refers to the time series trajectory formed by the direction and magnitude of cadence changes over multiple consecutive time periods, used to determine the user's output rhythm status;

[0065] Rhythm fluctuation status label refers to the classification result generated based on the trend change of cadence rate, which is used to identify whether the rhythm is stable, declining or fluctuating abnormally, and serves as one of the criteria for judging the training state.

[0066] The status determination module calls the rhythm fluctuation status label, combines the difference between the current flywheel speed and the average speed, and also refers to the changes between the current and recent average pedal pressure to determine whether there is a simultaneous power reduction and output pullback, and generates a stability determination signal.

[0067] Average rotational speed refers to the arithmetic mean of the flywheel rotational speed over a target time period, measured in revolutions per minute (RPM) or angular velocity (rad / s), and is collected in real time by the flywheel sensor.

[0068] Output retracement refers to the decrease in pedaling pressure applied by the user during cycling, reflecting a reduction in exercise intensity or signs of fatigue, and is supported by data provided by the pedal pressure sensor.

[0069] The stage control module calls the stability judgment signal, obtains the current training time, and matches it with the stage set time. It compares the deviation between the current cadence and the average cadence of the previous stage. If the conditions are met, it combines the current flywheel speed and pedal pressure signal to form the basis for stage transition and generates stage switching control command.

[0070] The stage setting time refers to the time threshold corresponding to each stage predefined by the system when setting up the training course, which is used as a time reference for switching training stages.

[0071] The stage transition criteria refer to the training stage switching trigger logic established by the system when it detects that the time and rhythm offset conditions are met simultaneously, which is used to determine whether to enter the next stage;

[0072] The stage switching control command refers to the target resistance parameter calculated based on the current flywheel speed and pedal force level after the system verification meets the stage transition criteria. The command is used to control the electronically controlled resistance unit to load the current resistance level.

[0073] The load adjustment module calls the stage switching control command to obtain the current resistance output level, processes the difference between the two, and, referring to the relationship between flywheel acceleration and pedal pressure, derives the control loading strategy and generates a resistance adjustment strategy template.

[0074] Flywheel acceleration refers to the rate of change of the flywheel angular velocity per unit time. It is obtained by differential analysis of continuous angular velocity data and is used to reflect the degree of matching between the dynamic state of the flywheel and the user's output.

[0075] The electronically controlled loading strategy refers to a set of logical strategies generated based on the current resistance state, stage switching instructions, and user output to adjust the output mode of the electronically controlled resistance unit.

[0076] The resistance adjustment strategy template refers to a standardized control model derived by the system based on the current training state to control the resistance adjustment process, which is used to guide the output rhythm and amplitude.

[0077] The output response module calls the resistance adjustment strategy template, combines the current heart rate change trend, establishes the load response weight, and generates the resistance response rhythm mode based on the flywheel state change and control delay index.

[0078] Load response weights are weighting parameters formed by combining the user's heart rate change trend, used to measure the degree of influence of the user's physiological state on the change in resistance output;

[0079] Flywheel state change refers to the trend of flywheel speed change per unit time, which is manifested as acceleration, deceleration or constant speed, and is used to judge the current operating response characteristics of the mechanical system.

[0080] The control delay index refers to the time delay between the issuance of a control command and the actual response of the electronically controlled resistance unit, which is used to correct the resistance output rhythm.

[0081] Resistance response rhythm mode refers to the output rhythm type generated by factors such as training status, user heart rate, flywheel changes, and system response delay, which is used to control the execution timing of resistance loading.

[0082] The rhythm fluctuation status labels include the direction of cadence change, the amplitude of cadence change, and the trend of cadence change rate. The stability judgment signals include the power change status, the output pullback status, and the rhythm stability level. The stage switching control commands include the stage switching basis, the stage switching time, and the switching validity indicator. The resistance adjustment strategy template includes the resistance output difference, the flywheel acceleration correlation, and the electronic control loading strategy. The resistance response rhythm mode includes the load response weight, the flywheel status change, and the control delay index.

[0083] Specifically, such as Figure 2 , 3 As shown, the cadence recognition module includes:

[0084] The cadence extraction submodule extracts cadence values ​​and time points within a time period based on the cadence signal and corresponding time information during the training process, calls up cadence change and time change information between consecutive time periods, calculates the cadence change rate, and obtains the cadence change rate value.

[0085] Based on the collected cadence signals and time information, data analysis is performed. First, the raw data is preprocessed, including using low-pass filtering to remove high-frequency interference, uniformly adjusting the sampling frequency to 100Hz, and aligning the timestamps of each data point (e.g., correcting 3.251 seconds downwards to 3 seconds). After this, the overall time axis is divided into segments of 1 second each. Within each time segment, the cadence values ​​of all sampling points are statistically analyzed, and the average value is taken as the cadence value corresponding to that time point. For example, if the cadence values ​​collected in the 3rd second are 92, 94, 91, and 93, then the average cadence value for that second is 92.5 RPM. This method constructs a time series and cadence value series arranged by second. Then, the rate of cadence change between adjacent time segments is calculated. By comparing the cadence difference and time difference between two adjacent moments, the rate of cadence change per second is obtained. If the cadence in the 3rd second is 92.5 RPM and the 4th second is 95.0 RPM, then the rate of change is 2.5 RPM per second. This process is repeated to calculate the rate for all time segments, forming a complete cadence change rate sequence, which serves as the basis for subsequent module analysis.

[0086] The trend recognition submodule constructs a sequence of change direction and change amplitude information for a continuous time period based on the cadence change rate value, compares the change direction in adjacent time periods to determine the continuity of the change, and calculates the trend offset rate by combining the change range of the change amplitude with the difference of the current amplitude, and obtains the trend offset rate value.

[0087] Based on the obtained cadence change rate sequence, the direction and amplitude of the change are determined segment by segment. The direction is determined by the sign of the rate: an increase is recorded as "increasing," a decrease as "decreasing," and zero as "unchanged." For example, if the rate sequence is 2.5, -1.2, 0, the directions are increasing, decreasing, and unchanged, respectively. The amplitude is calculated based on the absolute value of the rate; for example, -1.2 has an amplitude of 1.2 RPM per second. The amplitude is divided into intervals according to a preset amplitude threshold; for example, an amplitude greater than 2 is considered high amplitude, and less than or equal to 2 is considered low amplitude. Next, the directions of adjacent time intervals are compared. If the directions are consistent, it is considered a continuation; otherwise, it is considered a continuation. The concept of "consistency" indicates change. The continuity ratio can be calculated by statistically analyzing the number of continuous segments and the total number of segments. For example, if three out of five time periods are in the same direction, the continuity ratio is 75%. Then, the difference between adjacent amplitudes is determined. For example, if the current amplitude is 2.0 and the next amplitude is 0.5, the difference is 1.5 RPM per second. The amplitude fluctuation threshold is used to determine whether it is severe or mild. If it is higher than 1.5, it is severe; if it is less than or equal to 1.5, it is mild. Finally, the trend deviation rate is obtained by combining the continuity ratio and the amplitude difference. For example, when the amplitude difference is 2 and the continuity ratio is 75%, the deviation rate is 0.5. By traversing the entire time series in this way, a complete trend deviation rate sequence is obtained for processing in the next module.

[0088] The state determination submodule calls the trend offset rate value and the change direction sequence information to jointly determine the direction and offset of the current time period. Based on the direction change threshold and offset rate threshold in the rhythm fluctuation determination standard, it determines the rhythm state type and obtains the rhythm fluctuation state label.

[0089] Based on the joint analysis of trend offset rate and direction information, the number of direction changes within a period of time is first counted. A change of more than 2 times within 5 seconds is defined as frequent fluctuation, otherwise it is considered a stable state. Then, the degree of fluctuation of the trend offset rate within that time period is judged. If the offset rate value of a certain segment is greater than or equal to 1.0, it is recorded as high offset; otherwise, it is low offset. If a high offset state occurs once within a 5-second sequence, there is a strong trend change in that segment. The current direction information is combined with the offset state. For example, if the current direction is downward and the offset rate is high, and the number of direction changes is 3, it is judged as a fluctuating downward state. According to the preset state label rules, a stable direction with a low offset rate is marked as a stable state; frequent direction changes with a high offset rate are marked as violent fluctuation dynamics; and a continuously rising direction with a low offset is marked as a gently rising state. The above judgment logic covers each time period, outputting a complete rhythm fluctuation state label sequence.

[0090] Specifically, such as Figure 2 , 4 As shown, the status determination module includes:

[0091] The tag calling submodule extracts the fluctuation direction and intensity type corresponding to the current tag based on the rhythm fluctuation status tag. Combining the time axis order and tag continuity, it determines whether the rhythm status is in a phased change range and obtains the rhythm change range value.

[0092] Based on rhythmic fluctuation state labels, the direction and intensity level of fluctuation contained in the current label are extracted. The labels are then arranged in chronological order to construct a one-to-one mapping between time and labels. On this basis, the continuity of the label sequence is judged, primarily identifying whether the direction is consistent and whether the intensity exhibits stability or a gradual trend. If adjacent labels maintain the same direction and their intensity gradually increases or decreases, it is considered to have a phased fluctuation trend. For example, from the 10th to the 15th second, if the label sequence is medium-intensity increase, high-intensity increase, high-intensity increase, medium-intensity increase, low-intensity increase, and low-intensity flat, it can be identified as a fluctuating upward trend interval. Simultaneously, a time threshold for continuous label identification is set. 3 seconds is used to determine whether segments below this value constitute a stable interval. The maximum allowable interval between tag time points is further set to 1.5 seconds to determine whether the tags are continuous. If the interval between two adjacent tags does not exceed this value and their directional intensity characteristics are similar, they can be merged into a stage of change. For example, if the tags appear at the 5th and 6th seconds respectively, with an upward direction and medium and high intensities respectively, it is determined to be a continuous upward stage. The start and end time points, direction type, and average intensity level are recorded in this stage. By traversing and analyzing all tags on the timeline, a complete rhythm change interval sequence is constructed, in which each segment contains parameters such as unique number, direction, average intensity, and time span.

[0093] The speed difference calculation submodule calls the rhythm variation interval value. Based on the numerical difference between the current flywheel speed and the average flywheel speed within a set time period, it extracts the change amplitude between the current and recent average pedal pressure, calculates the synchronous change rate between the current output index and the reference value, and obtains the output change rate value.

[0094] After obtaining the rhythm variation interval value, the flywheel speed at the current moment is first read. For example, if the current time is the 10th second, the flywheel speed is 90 rpm. Then, within a set time period, such as a 5-second time window, the historical flywheel speed values ​​are extracted, which are 87, 89, 91, 88, and 90 rpm respectively. The average value is calculated to be 89 rpm, and the difference between the current value and the historical average is 1 rpm. Next, the average pedal pressure within the same time period is extracted. Assuming the current pedal pressure is 300 N and the historical average pressure is 280 N, the current pressure change is 20 N. Combining the above speed difference, the current output state is calculated. The degree of synchronization change between reference states is determined by setting a reference range based on the synchronization change judgment standard. If the pressure change corresponding to a unit speed difference is 20 N per rpm, the current synchronization change ratio can be calculated to be 0.8. A synchronization ratio between 0 and 0.5 indicates a low synchronization state, between 0.5 and 1.2 indicates a medium synchronization state, and above 1.2 indicates a high synchronization state. This result reflects the degree of coordination between the current output and the rhythm beat. This indicator is analyzed for each time period within the entire rhythm range to form a continuous output change rate sequence as the basis for subsequent stability judgment.

[0095] The stability judgment submodule identifies the direction and amplitude of output fluctuations based on the correspondence between the output rate of change value and the rhythm state change range, determines whether there is an overlapping range between the power reduction signal and the output pullback signal, and establishes a stability judgment signal.

[0096] After obtaining the output change rate value and rhythm change interval, the output change rate is divided into multiple continuous windows for analysis in chronological order. The window length is set to 5 seconds. Within each window, the average value and fluctuation amplitude of the output change rate are calculated. For example, if the output change rate is 0.7, 0.9, 1.2, 0.5, and 0.6 within a certain period, its standard fluctuation level is calculated. If this value is greater than a set threshold, such as 0.6, it is determined to be an output fluctuation state. Subsequently, the trend of the rhythm label corresponding to that window is analyzed. If the label direction frequently alternates, such as rising then falling and then rising again, accompanied by a sudden change in intensity, such as high intensity becoming low intensity, then it is considered... For rhythm fluctuation segments, time is aligned with the output fluctuation window. If the two time periods overlap by more than 50%, they are marked as fluctuation overlap areas. Further, it is determined whether the direction and output characteristics are consistent. If the output change trend is downward and the rhythm label direction is intensity reduction, it indicates that there is a signal of weakening power. If the output change shows repeated fluctuations and overall retreat, it is considered as an output retreat signal. If both the power weakening and retreat signals appear in the same time interval, it is considered as an unstable area. This area will be marked as a stability judgment signal, and the time period, output fluctuation value and rhythm trend information will be recorded as the basis for system prompts.

[0097] Specifically, such as Figure 2 , 5 As shown, the stage control module includes:

[0098] The time matching submodule calls the stability determination signal to obtain the current training time value. Based on the interval membership relationship between the start and end values ​​of the stage-defined time interval and the current training time value, it determines whether the current time falls within the range of a single specified stage and generates a stage matching marker value.

[0099] After invoking the stability determination signal, the actual time value during the current training process is first extracted, for example, the current training has lasted for 540 seconds. Then, based on the preset training stage time intervals, the start and end times of each stage are obtained one by one. For example, the warm-up stage is 0 to 300 seconds, the basic stage is 301 to 900 seconds, and the sprint stage is 901 to 1200 seconds. By comparing the current training time with the range of each stage interval, it is determined whether the current time value falls within a specific stage. If the current time is greater than the start time of the basic stage (301 seconds) and less than the end time of that stage (900 seconds), then it is determined that the current stage belongs to the basic stage. In this judgment logic, a linear time comparison method is used to establish time boundary thresholds for each stage and set a tolerance range, such as ±1 second, to avoid incorrect judgments caused by device sampling errors. The corresponding stage number value is set as a matching mark output in the judgment result. For example, the basic stage is marked as 2, the warm-up stage as 1, and the sprint stage as 3. The stage matching mark is output in numerical form for control logic calls. The time value is refreshed every 1 second during system operation and the above judgment process is re-executed, thereby realizing continuous identification of stage status. It is suitable for dynamic control scenarios of periodic and staged training plans.

[0100] The cadence offset submodule obtains the values ​​of the current cadence and the average cadence of the previous stage based on the stage matching mark value, calculates the difference between the two, and compares the difference with the set cadence offset threshold to obtain the cadence offset status value.

[0101] After identifying the current stage as the basic stage based on the stage matching marker value, the current real-time cadence value is extracted, and the average cadence value of the previous stage, i.e., the warm-up stage, is obtained. For example, if the cadence data recorded during the warm-up stage are 60, 62, 65, 61, and 63, the average value is calculated to be 62 rpm. If the current real-time cadence is 70 rpm, the difference between the two stages is 8 rpm, which is the offset. This offset is then compared with a preset offset threshold. If the threshold is set to 10 rpm, the current offset does not exceed the threshold range and is marked as normal. If the current cadence reaches 75 rpm, the difference is... If the cadence deviation is 13 rpm, exceeding the threshold, it is marked as an abnormal deviation. The threshold setting is based on the training mode and individual differences. It can be set to 5 rpm for light load, 10 rpm for moderate intensity, and 15 rpm for high intensity. The cadence deviation status value is output as a Boolean variable or a numerical label, for example, 0 indicates normal and 1 indicates abnormal deviation. The system updates and compares cadence data at each training time point to ensure that cadence fluctuations caused by rhythm or fatigue are captured during training phase switching. This process can identify potential rhythm change risks in real time and provide input basis for subsequent control logic.

[0102] The stage switching submodule extracts the conformity relationship of the three values ​​in the stage change boundary range based on the combined state characteristics between the pedal frequency offset state value, the current flywheel speed value, and the pedal pressure signal value, determines whether the current stage meets the switching conditions, and obtains the stage switching control command.

[0103] The system analyzes three data points: cadence deviation, flywheel speed, and pedal pressure. First, it reads the current flywheel speed (e.g., 95 rpm) and pedal pressure (e.g., 280 N). Simultaneously, it identifies and marks the current cadence deviation as abnormal. A phase switching decision is made by setting combined judgment conditions, such as an abnormal cadence deviation, speed exceeding 90 rpm, and pressure exceeding 250 N. If all three conditions are met, the phase switching condition is satisfied, and a phase switching control command is output. The judgment logic is based on a logical AND operation, outputting the command only when all conditions are met simultaneously. The flywheel speed threshold can be set based on the average speed of the current phase plus 10% as a boundary. For example, if the current average speed is 85 rpm, the threshold is 93.5 rpm. The pressure threshold can be set by referring to the user's weight multiplied by 3 N. For example, if the user weighs 70 kg, the pressure threshold is approximately 210 N. For high-intensity phases, this can be increased to over 250 N. During actual training, this phase switching process updates data every second, executes logical judgments, and outputs results. When a judgment result is satisfied, the control system is triggered to update the phase status, providing a switching basis for the rhythm guidance and equipment load adjustment modules.

[0104] Specifically, such as Figure 2 , 6 As shown, the load adjustment module includes:

[0105] The resistance difference submodule calls the stage switching control command value, obtains the current resistance output level value, calculates the difference based on the difference between the two values, compares the difference with the set resistance change threshold for interval, and generates the resistance deviation amplitude value.

[0106] After invoking the stage switching control command value, the system first obtains the system-set resistance baseline value based on the current stage number, and then obtains the current resistance output value. For example, if the current output resistance is 180 N·m and the resistance at the end of the previous stage was 150 N·m, the difference between the two is 30 N·m. The system uses this difference as the baseline value for the current resistance change, and then compares it with the preset resistance change threshold. The resistance change threshold is set according to the training level; for example, it is set to no more than 20 N·m for the beginner stage, 40 N·m for the intermediate stage, and relaxed to 60 N·m for the high-intensity stage. The system compares the current stage level with the set value. If the difference is within the set threshold range, it is marked as normal; if it exceeds the threshold, it is marked as abnormal. During the judgment process, the system divides the difference range into three levels: 0 to 20 N·m for low difference, 21 to 40 N·m for medium difference, and more than 40 N·m for high difference. The corresponding output resistance deviation amplitude values ​​are 0, 1, and 2, respectively. For example, if the difference is 30 N·m, it is in the medium difference range, and the output deviation amplitude value is 1. All calculation processes are executed immediately after the stage switch is completed to ensure the continuity of the resistance change process and the integrity of the difference control logic.

[0107] The electronic control relationship submodule obtains the flywheel acceleration value and pedal pressure signal value based on the resistance deviation amplitude value, calculates the numerical correlation coefficient between the flywheel acceleration value and pedal pressure signal value within the same interval, and makes a joint judgment based on the correlation coefficient and the resistance deviation amplitude value to obtain the load response judgment value.

[0108] After receiving the resistance deviation value, the current acceleration value of the flywheel and the current pressure signal value of the pedal are obtained, for example, the flywheel acceleration is 1.8 m / s². 2The pedal pressure is 290N. These two data points are used as a set of corresponding inputs. The system performs interval matching analysis on data samples from multiple consecutive time points, synchronously comparing the fluctuation trends of flywheel acceleration and pedal pressure in the current stage to analyze whether there is a trend correlation between the two. The correlation is determined by calculating the degree of synchronous change of the two sets of data. If the flywheel acceleration also increases when the pressure value increases in multiple time points, it is judged as a high correlation. The system generates a correlation level label based on the analysis results, for example, divided into five levels from 0 to 4. Level 4 indicates that the numerical trends are basically consistent, and level 0 indicates that the trends are opposite or there is no obvious correlation. Combining this level with the current resistance deviation value, the system constructs a two-dimensional combined relationship model. For example, if the deviation level is 2 and the correlation level is 4, a load response judgment value of 4 is output to indicate that the system is in a high load feedback state. If the deviation is 1 and the correlation level is 1, the output judgment value is 1 to indicate weak feedback. This response judgment value is updated in real time after each resistance adjustment to guide the generation of the next strategy response.

[0109] The strategy generation submodule matches the resistance output level coefficient corresponding to the differential electronic control loading type based on the load response judgment value, extracts the combination sequence of resistance output level coefficients under the current stage, and constructs a complete adjustment logic template to generate a resistance adjustment strategy template.

[0110] After receiving the load response judgment value, the system matches the corresponding load type from the preset electronic control load types. For example, if the response judgment value is 4, the system matches the high response level load model. This model contains multiple resistance output level coefficients. The system extracts the corresponding output coefficient sequence according to the stage number. For example, in the high response mode, the corresponding output coefficient for the middle stage is 1.4. If the current basic resistance is 180 N·m, multiplying it by 1.4 gives the target resistance output of 252 N·m. The system records this value and adds the coefficient value to the adjustment logic template. This template consists of the current stage number, load response value, load model type, and selected resistance coefficient. It is recombined and generated after each training stage change to guide the generation of control commands in real time. The strategy template also needs to adapt to continuously changing scenarios. For example, when the response level changes dynamically in the stage, the template should have a parameter update mechanism so that the output resistance can be adjusted in real time according to the response judgment value. In actual operation, the system re-evaluates the current state at fixed time intervals and reconstructs the adjustment strategy according to the template structure to ensure that the resistance output of the training equipment maintains a consistent logical relationship with the actual training intensity.

[0111] Specifically, such as Figure 2 , 7 As shown, the output response module includes:

[0112] The template call submodule calls the content of the resistance adjustment strategy template, extracts the resistance adjustment level value and adjustment time node sequence under the current stage, filters the adjustment level and time node that match the current motion cycle state, constructs the resistance adjustment sequence within the cycle, and generates the resistance adjustment sequence value.

[0113] The system invokes the resistance adjustment strategy template. First, based on the current training phase number, it extracts the set of resistance adjustment levels and the sequence of adjustment time points associated with that phase. For example, in phase 3, the template stores adjustment levels of 120, 140, and 160 N·m, and adjustment time points of 10, 30, and 50 seconds. Based on the real-time detected motion cycle state, the system determines that the current motion has reached the 28th second of the second cycle. It then selects nodes with time points less than or equal to 28 seconds as the current matching nodes, such as 10 seconds and 30 seconds, corresponding to adjustment levels of 120 and 140 N·m. The system then sorts the selected nodes chronologically and generates intermediate values ​​for smooth transitions between these known adjustment points. For example, if the 28-second mark is close to the 30-second mark, a transition value of two seconds needs to be added between the current point and the next adjustment point. The system can fill in the transition value of 130 N·m before the intermediate point of 140 N·m by increasing it by 10 N·m per second. The constructed adjustment sequence within the cycle consists of 5 sets of data, namely 120, 130, 140, 150 and 160 N·m, corresponding to time points of 10, 20, 30, 40 and 50 seconds, respectively. The system outputs the complete resistance adjustment sequence value of this cycle as the basis for resistance control in the current period. The whole process combines multiple links such as template parameter extraction, state matching, adjustment data screening and sequence interpolation construction, and processes them in combination with specific time points under actual operating conditions, thus completing the generation of an adjustment sequence synchronized with the cycle state.

[0114] The weight establishment submodule obtains the heart rate change trend value based on the resistance adjustment sequence value, compares the growth rate of the heart rate change trend value in adjacent time periods with the set heart rate response benchmark rate, adjusts the adjustment intensity level of the corresponding segment in the resistance adjustment sequence value according to the difference amplitude, and establishes the load response weight coefficient.

[0115] Based on the resistance regulation sequence values, the system retrieves real-time heart rate data sets for each stage of the training process and analyzes their trends between two consecutive time periods. For example, if the heart rate is 130 bpm at 20 seconds and increases to 150 bpm at 40 seconds, the increase is approximately 1 bpm per second. The system's baseline heart rate response rate is set at 0.8 bpm per second. By comparing the current increase rate with this baseline rate, the system determines that the increase is higher than expected and judges the current heart rate response to be too fast. It then locates the portion of the current regulation sequence value corresponding to that time period, for example, a resistance level of 140 N·m and a regulation level of 2. To address rapid heart rate changes, the system adjusts the regulation level for this segment to Level 3, corresponding to a resistance increase of 160 N·m. If the detected heart rate increase rate is lower than the set rate, the regulation level is lowered by one level. This adjustment process is based on the difference between each segment of heart rate change and the baseline rate. The adjustment results are used to establish a load response weighting coefficient, which represents the degree of interaction between the resistance regulation intensity and the heart rate response in each time period. For example, when the regulation intensity is increased from Level 2 to Level 3, the weighting coefficient is set to 1.5, and it is 1 when there is no adjustment. After the coefficient is constructed, it is saved by the system to the response model to guide the construction and updating of subsequent rhythm control strategies.

[0116] The rhythm generation submodule collects flywheel state change values ​​and control delay index values ​​based on the load response weighting coefficient. It calculates the ratio of flywheel state change values ​​and control delay index values ​​within the corresponding time period, and combines the ratio values ​​with the load response weighting coefficient to obtain the resistance response rhythm pattern.

[0117] Based on the resistance regulation sequence values ​​output by the previous module, the system retrieves real-time heart rate data sets for each stage of the training process and analyzes their trends between two consecutive time periods. For example, if the heart rate is 130 bpm at 20 seconds and increases to 150 bpm at 40 seconds, the growth trend is approximately 1 bpm per second. The system's set baseline heart rate response rate is 0.8 bpm per second. By comparing the current growth rate with this baseline rate, the system finds that the growth trend is higher than expected. Based on this, the system determines that the current heart rate response is too fast. Subsequently, it locates the portion of the current regulation sequence value corresponding to this time period, for example, a resistance level of 140 N·m and a regulation level of [missing information]. Level 2: To address excessively rapid heart rate changes, the system adjusts this adjustment level to Level 3, corresponding to an increase in resistance to 160 N·m. If the detected heart rate increase rate is lower than the set rate, the adjustment level is lowered by one level. This adjustment process is based on the difference between each heart rate change and the baseline rate. The adjustment result is used to establish a load response weighting coefficient, which represents the degree of interaction between resistance adjustment intensity and heart rate response in each time period. For example, when the adjustment intensity is increased from Level 2 to Level 3, the weighting coefficient is set to 1.5, and it is 1 when there is no adjustment. After the coefficient is constructed, it is saved by the system to the response model to guide the construction and updating of subsequent rhythm control strategies.

[0118] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multifunctional exercise bike system, characterized in that, The system includes: The cadence recognition module acquires cadence values ​​and time information during the training process, analyzes the cadence rate trend within a continuous time period, identifies the rhythm state based on the direction and amplitude of change, and generates rhythm fluctuation state labels. The status determination module calls the rhythm fluctuation status label, combines the difference between the current and average flywheel speed, and refers to the change between the current and recent average pedal pressure to determine whether there is a power reduction and output pullback, and generates a stability determination signal. The stage control module calls the stability judgment signal to obtain the current training time, matches it with the stage set time, compares the deviation of the current average pedal frequency from the previous stage, and when the conditions are met, generates a stage switching control command by combining the flywheel speed and pedal pressure. The load adjustment module calls the stage switching control command to obtain the current resistance output level and analyze the difference. Referring to the relationship between flywheel acceleration and pedal pressure, it derives the control loading strategy and generates a resistance adjustment strategy template. The output response module calls the resistance adjustment strategy template, combines the heart rate change trend, establishes the load response weight, and generates the resistance response rhythm mode based on the flywheel state and control delay. The output response module includes: The template calling submodule calls the content of the resistance adjustment strategy template, extracts the resistance adjustment level value and adjustment time node sequence under the current stage, filters the adjustment level and time node that match the current motion cycle state, constructs the resistance adjustment sequence within the cycle, and generates the resistance adjustment sequence value. The weight establishment submodule obtains the heart rate change trend value based on the resistance adjustment sequence value, compares the growth rate of the heart rate change trend value in adjacent time periods with the set heart rate response benchmark rate, adjusts the adjustment intensity level of the corresponding segment in the resistance adjustment sequence value according to the difference amplitude, and establishes the load response weight coefficient. The rhythm generation submodule collects flywheel state change values ​​and control delay index values ​​based on the load response weighting coefficient, calculates the ratio of flywheel state change values ​​and control delay index values ​​within the corresponding time period, and combines the ratio values ​​with the load response weighting coefficient to obtain the resistance response rhythm pattern. The flywheel acceleration refers to the rate of change of the flywheel angular velocity per unit time, which is obtained by differential analysis of continuous angular velocity data. The electronically controlled loading strategy refers to a set of logical strategies generated based on the current resistance state, stage switching instructions, and user output to adjust the output mode of the electronically controlled resistance unit. The resistance adjustment strategy template refers to the standardized control model derived by the system based on the current training state for controlling the resistance adjustment process. The load response weight refers to the weighting parameter formed by combining the user's heart rate change trend; The flywheel state refers to the trend of the flywheel's rotational speed change per unit time, which is manifested as acceleration, deceleration, or constant speed. The control delay refers to the time delay between the issuance of a control command and the actual response of the electronically controlled resistance unit. The resistance response rhythm pattern refers to the output rhythm type generated by factors such as training status, user heart rate, flywheel changes, and system response delay.

2. The multifunctional exercise bike system according to claim 1, characterized in that, The rhythm fluctuation status label includes the direction of cadence change, the amplitude of cadence change, and the trend of cadence change rate. The stability judgment signal includes the power change status, the output pullback status, and the rhythm stability level. The stage switching control command includes the stage switching basis, the stage switching time point, and the switching validity indicator. The resistance adjustment strategy template includes resistance output difference, flywheel acceleration correlation, and electronic control loading strategy.

3. The multifunctional exercise bike system according to claim 1, characterized in that, The cadence recognition module includes: The cadence extraction submodule extracts cadence values ​​and time points within a time period based on the cadence signal and corresponding time information during the training process, calls up cadence change and time change information between consecutive time periods, calculates the cadence change rate, and obtains the cadence change rate value. The trend recognition submodule constructs a sequence of change direction and change amplitude information for a continuous time period based on the cadence change rate value, compares the change direction in adjacent time periods to determine the continuity of change, and calculates the trend offset rate by combining the change range of the change amplitude with the difference of the current amplitude, and obtains the trend offset rate value. The state determination submodule calls the trend offset rate value and change direction sequence information to jointly determine the direction and offset of the current time period. Based on the direction change threshold and offset rate threshold in the rhythm fluctuation determination standard, it determines the rhythm state type and obtains the rhythm fluctuation state label.

4. The multifunctional exercise bike system according to claim 3, characterized in that, The status determination module includes: The tag calling submodule extracts the fluctuation direction and intensity type corresponding to the current tag based on the rhythm fluctuation state tag, and determines whether the rhythm state is in a stage change range by combining the time axis sequence and tag continuity, and obtains the rhythm change range value. The speed difference calculation submodule calls the rhythm variation interval value, extracts the change amplitude between the current flywheel speed and the average flywheel speed within the set time period based on the numerical difference between the current flywheel speed and the recent average pedal pressure, calculates the synchronous change rate between the current output index and the reference value, and obtains the output change rate value. The stability judgment submodule identifies the direction and amplitude of output fluctuations based on the correspondence between the output change rate value and the rhythm state change range, determines whether there is an overlapping range between the power reduction signal and the output pullback signal, and establishes a stability judgment signal.

5. A multifunctional exercise bike system according to claim 4, characterized in that, The stage control module includes: The time matching submodule calls the stability determination signal to obtain the current training time value. Based on the interval membership relationship between the start and end values ​​of the stage-defined time interval and the current training time value, it determines whether the current time falls within a single specified stage range and generates a stage matching marker value. The cadence offset submodule obtains the values ​​of the current cadence and the average cadence of the previous stage based on the stage matching mark value, calculates the difference between the two, and compares the difference with the set cadence offset threshold to obtain the cadence offset status value. The stage switching submodule extracts the conformity relationship of the three values ​​in the stage change boundary range based on the combined state characteristics between the pedal frequency offset state value, the current flywheel speed value, and the pedal pressure signal value, determines whether the current stage meets the switching conditions, and obtains the stage switching control command.

6. A multifunctional exercise bike system according to claim 5, characterized in that, The load adjustment module includes: The resistance difference submodule calls the stage switching control command value to obtain the current resistance output level value, calculates the difference based on the difference between the two values, compares the difference with the set resistance change threshold for interval comparison, and generates a resistance deviation amplitude value. The electronic control relationship submodule obtains the flywheel acceleration value and the pedal pressure signal value based on the resistance deviation amplitude value, calculates the numerical correlation coefficient between the flywheel acceleration value and the pedal pressure signal value within the same interval, and makes a joint judgment based on the correlation coefficient and the resistance deviation amplitude value to obtain the load response judgment value. The strategy generation submodule matches the resistance output level coefficient corresponding to the differential electric control loading type based on the load response judgment value, extracts the combination sequence of resistance output level coefficients under the current stage, constructs a complete adjustment logic template, and generates a resistance adjustment strategy template.

7. A multifunctional exercise bike system according to claim 1, characterized in that, The cadence value refers to the number of times a user's foot rotates on the pedals of a stationary bike per unit time, expressed in revolutions per minute, and is collected by a cadence sensor installed on the pedal axle or freewheel; The rate trend refers to the time series trajectory formed by the direction and magnitude of the increase or decrease in cadence over multiple consecutive time periods. The rhythm fluctuation status label refers to the classification result generated based on the trend change of cadence rate, which is used to identify whether the rhythm is stable, declining or fluctuating abnormally, and serves as one of the criteria for judging the training state.

8. A multifunctional exercise bike system according to claim 1, characterized in that, The average flywheel speed refers to the arithmetic mean of the flywheel rotation speed over the target time period, expressed in revolutions per minute or angular velocity, and is collected in real time by the flywheel sensing device. The output pullback refers to the decrease in pedaling pressure applied by the user during cycling, reflecting a reduction in exercise intensity or signs of fatigue, and is supported by data provided by the pedal pressure sensor. The stage setting time refers to the time threshold corresponding to each stage predefined by the system when setting up the training course; The stage switching control command refers to the target resistance parameter calculated based on the current flywheel speed and pedal force level after the system verifies that the stage switching criteria have been met.

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