Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/48—Other medical applications
  • A61B5/4866—Evaluating metabolism
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/22—Ergometry; Measuring muscular strength or the force of a muscular blow
  • A61B5/221—Ergometry, e.g. by using bicycle type apparatus
  • A61B5/222—Ergometry, e.g. by using bicycle type apparatus combined with detection or measurement of physiological parameters, e.g. heart rate
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
  • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
  • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
  • G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
  • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B2503/00—Evaluating a particular growth phase or type of persons or animals
  • A61B2503/10—Athletes
• • A—HUMAN NECESSITIES
  • A63—SPORTS; GAMES; AMUSEMENTS
  • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
  • A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
  • A63B24/0075—Means for generating exercise programmes or schemes, e.g. computerized virtual trainer, e.g. using expert databases
  • A63B2024/0078—Exercise efforts programmed as a function of time
• • A—HUMAN NECESSITIES
  • A63—SPORTS; GAMES; AMUSEMENTS
  • A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
  • A63B24/00—Electric or electronic controls for exercising apparatus of preceding groups; Controlling or monitoring of exercises, sportive games, training or athletic performances
  • A63B24/0087—Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load
  • A63B2024/0093—Electric or electronic controls for exercising apparatus of groups A63B21/00 - A63B23/00, e.g. controlling load the load of the exercise apparatus being controlled by performance parameters, e.g. distance or speed
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
  • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Definitions

• the present invention relates to a method and a device for the control of a metabolic.
• the invention also relates to a computer program product and a recording medium comprising such a program.
• the invention can be used in particular in the context of monitoring a person exerting an effort during an exercise, for example during a sports exercise or during a medical examination.
• Many applications require the determination of the metabolic state of an individual providing physical effort. Such applications include for example the monitoring of a person during a sports exercise or during rehabilitation, potentially under the supervision of a third person.
• the above steps are repeated at regular intervals.
• the updating of the value of the correction can advantageously be carried out at a slower rate than that of the error, for example at a rate slower by a factor greater than at least one order of magnitude.
• the reference value of the index is determined for a time k as a function of one or more previously determined passage points of said index over time.
• the metabolic law is a PID regulation law depending on the quantity of oxygen consumed and the quantity of carbon dioxide produced by the person.
• the quantities of oxygen consumed and of carbon dioxide produced are obtained by an estimate based on a measurement of a power supplied by the person or an estimate of the power supplied by the person.
• the objective to be achieved over time comprises the total energy to be supplied by the person during the exercise.
• the adjustment of the process for obtaining the power setpoint is carried out at the level of the error, of the metabolic control law or of the value of the power setpoint.
• the signal representing the power setpoint is used to control the load of a device used by the person to provide mechanical power.
• the signal representative of the power setpoint is implemented to generate a signal intended to be displayed in the form of an indication relating to the power setpoint in order to guide the individual in the effort to provide.
• the power setpoint is translated in the form of an increment or a decrement.
• the determination of one of the plurality of values of the correction as a function of at least one objective to be achieved over time comprises the resolution of a problem of optimization of the correction value under the constraint of at least one objective to be achieved over time.
• a device for monitoring the metabolic state of a person in the context of an exercise during which the person provides mechanical power, said metabolic state being represented by a physiological index said device comprising a processor configured to implement the above method.
• a recording medium readable by a device comprising a processor, the medium comprising instructions which, when executed by the processor, lead to the implementation, by the device, of steps of the above method.
• a computer program product comprising instructions which, when the program is executed by a processor of a device, cause the device to implement the steps of the method above.
• - figure 1 is a block diagram of a system according to an exemplary embodiment
• - Figure 2 is a block diagram of an embodiment of the control module and the prognosis module of Figure 1
• - Figure 3 is a flowchart of the main steps implemented by the control module and the prognosis module of Figure 1
• – Figure 4 is a block diagram of a device suitable for the implementation of certain embodiments
• – Figure 5 is a graph of the Respiratory Exchange Ratio, RER, in an application to an indoor cycle
• - figure 6 is a graph of the power of the motor load of the bicycle, of the power supplied by the cyclist and of the calories consumed within the framework of the application of figure 5;
• each block of a block diagram or each step of an algorigram can represent a module or even a portion of software code comprising instructions for the implementation of one or more functions. According to certain implementations, the order of the blocks or the steps can be changed, or even the corresponding functions can be implemented in parallel.
• the process blocks or steps can be implemented using circuits, software or a combination of circuits and software, and this in a centralized way, or in a distributed way, for all or part of the blocks or steps.
• a suitable data processing system or device comprises for example a combination of software code and circuits, such as a processor, controller or other circuit suitable for executing the software code.
• the processor or controller causes the system or device to implement all or part of the functionalities of the blocks and/or steps of the processes or methods according to the example embodiments.
• the software code can be stored in a readable memory or medium accessible directly or through another module by the processor or controller.
• a system according to an exemplary embodiment is illustrated by the block diagram of FIG. 1. This system allows the monitoring of one or more physiological indices.
• a non-limiting example of a physiological index is the Respiratory Exchange Ratio, RER.
• the system of figure 1 comprises - A first block ('A') intended to provide an estimate of oxygen, O2, consumed and of carbon dioxide, CO2, produced, on the basis for example of a measurement or a estimation of the mechanical power supplied by an individual during a effort.
• Block A provides at the output in particular values of at least one index depending on the estimates of the quantities of O2 and of CO2.
• a second block ('B') exercising a function of prediction and control, and determining actions – for example the increase or decrease in the intensity of the effort to be provided – to follow a desired trajectory of a or more clues.
• Block A comprises an estimator 101.
• the estimator receives as input signals representative of data making it possible to directly or indirectly determine a mechanical power supplied by the individual.
• the signals representative of these data are produced by one or more sensors 104, 106, 108 and 110.
• the estimator 101 outputs the quantity of oxygen, O2, consumed 112 and the quantity of dioxide of carbon, CO2, produced 113.
• the estimates of the quantities of oxygen consumed 112 and of carbon dioxide produced 113 are obtained by applying the following model: [Equation 1] where the constants ⁇ i , ⁇ j and w0 are obtained for example by linear regression from previously measured data of VO2 and VCO2 for different mechanical powers u(k).
• the estimator also supplies the quantity of carbon dioxide produced in excess 114, a value that can be processed by a monitoring and/or diagnostic device integrated or external to the device illustrated by FIG.
• the mechanical power is for example the power produced by the actuation by the individual of a bicycle crankset or of another sporting device requiring mechanical actuation.
• Mechanical power can also be that produced by the individual without a device, simply by engaging in physical activity such as running.
• the mode of production of the mechanical power influences the choice of the sensor(s): if the power is supplied via a suitable sports device such as an exercise bike, the power can be obtained directly by a power 104 connected to the sports device in a manner known per se (a torque or cadence sensor for example), or via a pre-existing module on said device which provides the information directly. It is, in any case, possible to indirectly obtain an estimate of the power provided by the individual by measuring parameters related to the individual, for example the speed of movement, the heart rate and/or the oxygen saturation of the blood of the individual.
• the estimate of the mechanical power denoted u e (k)
• u e (k) could be obtained for example as a quadratic function of the heart rate, HR, by the relationship: [Equation 2] or, as a function of the speed of movement, v, by the relation: [Equation 3] where the coefficients ci are for example obtained by linear regression on the basis of real measurements of heart rates, speeds and mechanical powers.
• Figure 1 shows a heart rate sensor 106 providing a signal carrying heart rate data 107, as well as other sensors 108 providing signals carrying appropriate data 109. It is not necessary to have more than one piece of information to determine the potency. Optionally, having data from several sensors can make it possible to refine the estimation of the mechanical power.
• the environmental parameters include for example one or more of: temperature, location or altitude – these parameters can intervene in the model applied by the estimator 101 to obtain the output data. Indeed, if it is desired to monitor the volumes of O2 and CO2, these volumes depend on the temperature and the atmospheric pressure (the latter being able for example to be obtained from an atmospheric pressure sensor or on an estimate based on altitude). The person skilled in the art will choose, depending on the precise context, the number and the nature of the sensors to be used.
• the sensors implemented may comprise one or more of a heart rate monitor and a blood oxygen saturation sensor.
• Current connected watches also generally have an altimeter, a thermometer and means of geolocation.
• the estimator can be qualified as a 'virtual sensor' because in combination with the data from the real sensor(s), it provides estimates that could be provided directly by an appropriate device such as an ergospirometer.
• Block A of FIG. 1 further comprises an interface module 115 intended for interfacing between the user of the system and the estimator 101 through a connection 118.
• the user can be the individual exerting the effort or another person, for example a sports coach or a medically qualified person.
• the interface module 115 receives commands 116 from the user as input and provides data 117, for example in the form of a display of adjustment parameters and/or the quantities or volumes of oxygen 112 and carbon dioxide. carbon 113 and can be presented in various ways (instantaneous values, evolution over time, etc.).
• the commands entered by the user include, for example, a choice of personal parameters specific to the individual exerting the effort.
• An exchange analysis module 120 receives as input the quantities of oxygen consumed 112 and of carbon dioxide produced 113 and provides as output values 121 representative of one or more physiological indices, such as, without limitation, the Ratio of Respiratory Exchanges (RER), the metabolic rate (in kcal per unit of time), the percentages of consumption of carbohydrates, lipids and proteins.
• RER Ratio of Respiratory Exchanges
• the implementation of the Respiratory Exchange Ratio will be detailed later.
• the metabolic rate, MR can for example be obtained by applying Weir's formula: [Equation 4]
• Metabolic rate (in kcal per second) (3.94702 + 1.117CO2)/60 where VO2 is the volume of oxygen consumed in liters per minute and VCO2 is the volume of carbon dioxide produced in liters per minute.
• the carbohydrate, fat and protein consumption percentages are obtained from formulas known to those skilled in the art. In this regard, we can cite the equations published by Weir, JB de V. on August 1, 1949 in "New methods for calculating the metabolic rate with special reference to protein metabolism” (whose title in English is: “New methods for calculating metabolic rate with special reference to protein metabolism") - published in The Journal of Physiology. 109 (1-2): 1-9. doi:10.1113/jphysiol.1949.
• Kcal per second 5.047% + 4.463y + 4.735z
• x is the percentage of carbohydrates, y that of proteins and z that of lipids.
• the exchange analysis module 120 is optionally connected to a display module
• the display module 122 allows the individual exerting the effort - and/or another person - to view the instantaneous values of the index or indices and their evolution over time.
• the values 121 produced by the gas exchange analysis module 120 serve as input on the one hand to a control module 123 and to a prognosis module 124, these last two modules both forming part of block B.
• the control module 123 also receives data 125, elaborated by a C interface module 126 from data 127. These data 127 can be supplied by the individual exerting the effort and/or another person, or even be read from a memory or obtained elsewhere. According to an exemplary embodiment, the data 127 includes one or more desired passage points of the index or indices.
• the data 125 supplied by the module 126 to the control module 123 are reference values—or setpoint values—of the index or indices, at a time k.
• the control module also receives data 136 from the prognosis module and performs the actions necessary for the index(es) to follow the established crossing points within an acceptable margin.
• the control module also receives data 136 from the prognosis module and performs the actions necessary for the index(es) to follow
• Modules 126 and 128 are also part of Block B.
• these modules or devices may include, where appropriate, a module for managing the intensity of the exercise performed by the individual controlled by the signal 129.
• the adjustment can be made by incrementing or decrementing the load or the braking (for a bicycle) and/or the inclination (for a running device) of the sports apparatus.
• these modules or devices comprise a means of communicating information to the individual exerting the effort to indicate to him the level at which he is located in relation to the desired passage points and/or instructions to be follow, for example acceleration (increment) or deceleration (decrement), in order to allow him to adapt his effort, both in relation to an overall objective to be achieved and in relation to the chosen passage points.
• This device provides for example an audio or visual signal in response to the signal 130.
• the device can in particular be a mobile telephone or a connected watch worn by the individual exerting the effort.
• the prognosis module 124 receives the values of index(es) 121 from the gas exchange analyzer and the power setpoint 134 from the control module 123.
• the prognosis module makes a prediction of the future values of the index(es) and responsively determines adjustments to exercise intensity to meet the desired level of performance.
• this level of performance 131 is provided by the individual exerting the effort or the user via the interface module C 126.
• the level of performance is for example the number of calories to be burned during the exercise as a whole.
• Performance level can be seen as a longer-term objective than tracking desired benchmarks for an index.
• the interface modules E 122 and C 126 are for example touch screens but can be implemented using other technologies making it possible to present data and to receive input data.
• the two interface modules are combined into a single input/output module, for example a single touch screen.
• the desired passage points of the index or indices can also be obtained by other means, for example by being read in a memory, following a pre-established program, etc.
• the system also comprises a power supply 132.
• the system also comprises a telemetry module 133.
• the components of the system of FIG. 1 can be included in a single physical device or be distributed over several devices.
• the sensors can be remote and communicate with the estimator by a wired or wireless link – for example, if a heart rate sensor is used, the latter can be attached to a belt worn by the user. individual whose metabolic reference is to be followed.
• the display module and/or the E and C interface modules can be external to a device comprising for example the data processing and control modules, such as the estimator 101, the gas exchange analyzer and the control and prognosis modules.
• the operation of the control module 123 and of the prognosis module 124 will now be described in relation to the block diagram of FIG. 2. This block diagram takes up certain elements of FIG.
• the modules 123 and 124 are intended to follow, in real time, at least one physiological index by acting on the power u(k) that must be provided an individual at a given instant k.
• the time variable k is discrete.
• e(k) will denote the tracking error between the measured or estimated index 121 (denoted Index) and the setpoint value (denoted Index ref ) at time k.
• the C interface module 126 provides a reference value per value of the temporal variable k, for example by interpolation, linear or other, between the defined passage values or by implementing another function allowing to generate intermediate points and to pass approximately by said waypoints.
• the control module 123 comprises a metabolic controller 203 implementing a metabolic control law based on a PID (proportional, integral, derivative) regulator.
• PID proportional, integral, derivative
• Other types of regulators adapted to follow state constraints can also be implemented instead of a PID regulator.
• VO2(k) and VCO2(k) designate respectively the volume of oxygen consumed at time k and the volume of CO2 produced at time k.
• any linear combination of VO2(k) and VCO2(k) can be regulated by the metabolic controller according to the present example embodiment.
• RER Respiratory Exchange Ratio
• Index ref (k) RER ref (k)
• the RER is defined as the ratio between VCO2 and VO2, at normal conditions of temperature and pressure.
• the corrective term is represented by the reference 136 and is added to the reference value of the index, Index ref (k), at the level of adder 204 (path (a) of reference 136).
• Index ref (k) the index of the index
• the prognosis module generates a corrective power term, which will be used to correct (206) the output of the metabolic controller and thus adjust the power setpoint (path (c) of reference 136).
• the prognosis module modifies the constants kp, ki, kd of equation 5 above (path (b) of reference 136).
• the metabolic controller directly receives the decisions of the post-prognosis decision module and acts on the command interface 128 to adapt the commands 129 accordingly.
• the prediction module 202 takes into consideration the current metabolic state (O2 or CO2 measured or estimated) via the current value 121 of the index provided by the block A (or directly the outputs 112 or 113), the output 134 u(k) corresponding to the application of the control law given by equation 5 plus the corrective term 136 at the output of the decision module 201, as well as the corrective term 136 itself.
• the prediction module performs a simulation of the possible evolutions of the index according to different values of the corrective term, and this on the basis of the mathematical model already implemented by the estimator 101 and linking the power supplied to the quantities of oxygen and of carbon dioxide and/or their volumes.
• the prediction module simulates the different possible trajectories of oxygen consumed and carbon dioxide produced on the basis of equation 1, which incorporates the metabolic control law (equation 5), by determining the values of oxygen and of carbon dioxide attainable by acting on u(k) via the corrective term ⁇ u(k).
• equation 5 the metabolic control law
• the post-prognosis decision module 201 takes into account a long-term objective (including the performance level 131 of the exercise is an example) and the result of the simulations performed by the prediction module 202, in the form of the possible trajectories (predicted) based on the metabolic control law (equation and different choices of ⁇ u(k) (increments or decrements).
• the choice of the corrective term is made taking into account the long-term objective.
• the prediction module launches a family simulations to establish the possible values of the energy consumed after a given time or a given distance, and according to the current operating conditions of the metabolic law.
• the energy consumed (kcal), denoted Ec can be taken as the cumulative sum of the expected metabolic rate.
• MR MRref - e(k), with e(k) a random variable which changes all along the prediction according to the func tion of the metabolic control law already in operation and on the basis of the mathematical model implemented which gives O2(k) and CO2(k) as a function of u(k)
• the consumed energy Ec can be predicted as the following cumulative sum: [Equation 13] where Ts (sampling time) is a constant equal to the time duration between instant k and instant k+1.
• the decision module solves a robust or stochastic optimization problem.
• the problem is for example to enforce a constraint on the long-term objective by minimizing a performance criterion, in the form of a function L.
• the decision variable which makes it possible to solve the optimization problem ⁇ which can, according to one of the paths (a), (b), (c) chosen, be ⁇ u, or a vector of the parameters metabolic law (kp, ki, kd).
• the optimization problem can be written in the following form: [Equation.14] where ⁇ will take the desired form (for example Ec in the context of the example where it is sought to guarantee the energy consumed).
• the constraint to be respected takes the following form: Probability(Ec(T_final)>E_target)>Prob_target where E_target represents the long-term objective and Prob_target represents the probability that the constraint is guaranteed.
• the choice of Prob_target depends on the desired level of guarantee.
• the energy consumed can represent the overall number of kilocalories invested, but can alternatively represent the energy consumed relating to one among lipids, carbohydrates, proteins instead of the total energy.
• the cost function L(.) could simply be the integral of e(k) 2 , because this error would depend on the choice on ⁇ u, ⁇ ⁇ or the vector of the parameters of the metabolic law (kp, k i , k d ). This optimization problem can be solved for example by using robust or stochastic optimization methods known elsewhere.
• the decision of the post-prognostic module is made at a rate lower than that at which the metabolic controller outputs u0(k) values. For example, ⁇ u(k) is updated once per minute while u0(k) is updated every second.
• 3 is an algogram of the main steps implemented by block A:
• a first step 301 the calculation of the error e(k) on the index with respect to a reference value of the index at time k is achieved.
• a metabolic law is applied to obtain a power setpoint to minimize the error.
• a prediction of the evolution of the index for a plurality of values of a correction to be applied within the framework of the determination of the power setpoint is carried out.
• one of the plurality of correction values is chosen according to at least one objective to be achieved over time.
• the value of the correction is applied to adjust the power control obtaining process.
• the correction is applied to the level of the error, of the metabolic control law or of the value of the power setpoint.
• the same value of the correction can be applied for several consecutive cycles of evaluation of the error and adjustment of the process for obtaining the power setpoint. In this case, it is not necessary to perform steps 303 and 304 as frequently.
• a signal representative of said power setpoint is generated.
• Figure 4 is a block diagram of a device 400 configured to implement the steps of the method of Figure 3 and/or implement the functional blocks described in conjunction with Figures 1 and 2.
• the device includes a processor 401, a volatile memory 402, a non-volatile memory 403, the latter comprising instructions 404 which, when executed by the processor, lead the device to implement the steps and/or to implement the functional blocks mentioned above.
• the various components are linked by a communication bus 405.
• the device may include other components or interfaces 406 to other components, depending on the implementation.
• Processor 401 may take any suitable form - one or more microprocessors, one or more microcontrollers, or a combination thereof.
• Volatile memory 402 is used for temporary storage of data.
• Nonvolatile memory 403 may include a hard disk, static memory, or other form of long-term storage.
• Non-volatile memory stores implementation instructions, it can also store an operating system and/or applications.
• the device is one of a computer or a connected watch or another device carried by the individual, such as for example a mobile telephone.
• the metabolic controller 203 has the function of minimizing the error e(k) at all times.
• the error is not always zero, in particular due to unpredictable disturbances (meteorological phenomena such as wind, traffic conditions, etc.), or even a non-compliant response by the individual in relation to the effort required. .
• the prognosis module 124 by taking long-term objectives into account, makes it possible to limit the impact of such disturbances.
• the graphs of FIGS. 5 and 6 illustrate the behavior of the RER when it is controlled as previously described, in the specific application to an indoor cycle.
• the cyclist provides a mechanical power imposed by the load of the motor of the bicycle and the control device varies the load of the motor to follow a reference value of the index, namely in this specific case, a constant value of the RER at 0.91 . It can be seen on the graph in figure 5 that after a transient response of the physiological variables, at approximately four minutes, the RER stabilizes around a value close to the reference value.
• the curves in FIG. 6 respectively illustrate the evolution over time of the power supplied by the cyclist, of the number of calories consumed and of the engine load adjusted progressively by the control device.
• FIG. 7 is a graph illustrating the evolution over time of the percentage of fat burned in the application of FIG. 5 and FIG.
• FIG. 8 is a graph illustrating the evolution over time of the rate of total kilocalories burned per second and the rate of kilocalories per second resulting from the fat burned in the application of FIG. fat, or total calories) as part of the predictions and to decide whether to increase or decrease the effort level / power setpoint to achieve long-term goals, e.g. a desired amount of calories burned at the end of the exercise, either from calories resulting from fat, or from calories without taking into account the nature of the energy source.

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