Physical fitness assessment using blood flow restriction

Abstract

In a first aspect, a multifunctional system for restricting blood flow of a limb, is disclosed. The system comprises an inflatable cuff configured to allow blood flow in the limb and to restrict blood flow, a pressure equipment being in fluid communication with the inflatable cuff, and a control unit configured to command the pressure equipment to set an inner cuff pressure, receive arterial oxygen data from an arterial oxygen sensor, and tissue oxygenation data from a tissue oxygenation sensor. The control unit is further configured to apply an algorithm to obtain venous oxygen data. In a further aspect, a method for operating the multifunctional system for restricting blood flow of a limb, is provided.

Description

[0001] PHYSICAL FITNESS ASSESSMENT USING BLOOD FLOW RESTRICTION

[0002] The present application claims the benefit and priority of EP23383021.5, filed on October 4, 2023.

[0003] The present disclosure relates to systems for restricting blood flow of a limb and methods for operating the systems.

[0004] BACKGROUND

[0005] Regular monitoring of the cardiovascular system is a recommended activity that may help to ensure adequate levels of health. Devices such as sphygmomanometers or blood pressure monitors, including inflatable cuffs, are used to measure blood pressure. This is usually done in a non-intrusive way.

[0006] Blood flow studies can also be done on limbs using inflatable cuffs. For example, blood reperfusion studies can be done by applying a restriction on the limb and releasing pressure afterwards. The time it takes for blood to flow back into the blood vessels of the limb can be measured. These studies can be performed on patients or elite athletes.

[0007] In the case of elite athletes, it is necessary to estimate their actual physical fitness and performance potential. Intrusive techniques can be used by introducing catheters to obtain blood samples and measure directly oxygen delivery and utilization, by assessing arteriovenous differences in oxygen content combined with the measurement of blood flow. The combined assessment of arterial and venous O2 content may allow the calculation of oxygen extraction, which, in itself, may be a significant variable related to health status and performance potential.

[0008] Therefore, devices that are used to assess some aspects related to the performance or physical fitness of an athlete or a patient involve the use of intrusive devices and techniques. This entails discomfort for the athlete or patient and may require the presence of qualified personnel, with the results obtained after some delay.

[0009] The present disclosure provides examples of systems and methods that at least partially resolve some of the aforementioned disadvantages. SUMMARY

[0010] In a first aspect, a multifunctional system for restricting blood flow of a limb, is disclosed. The system comprises an inflatable cuff configured to allow blood flow in the limb at a free-circulation state and to restrict blood flow in the limb at a restricting state. The system further comprises pressure equipment in fluid communication with the inflatable cuff, a tissue oxygenation sensor configured to gather tissue oxygenation data of a tissue of the limb, and an arterial oxygen sensor configured to gather the arterial oxygen data. The system also comprises a control unit configured to command the pressure source to set an inner cuff pressure at least at a predetermined restricting state pressure, receive first arterial oxygen data related to the free-circulation state, receive tissue oxygenation data related to the restricting state, receive second arterial oxygen data related to the restricting state, and determine a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value. The control unit is also configured to apply an algorithm configured to produce an output related to venous oxygen data of the main vein draining the limb or one of its tributaries, wherein the algorithm is fed with the first arterial oxygen data, the restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0011] According to this aspect, venous oxygen data of the main vein draining the limb and / or one of its tributaries may be obtained by non-invasive measurements.

[0012] The presence of qualified personnel may be reduced, and the results may be obtained relatively faster.

[0013] In a further aspect, a method for operating a multifunctional system for restricting blood flow of a limb, is disclosed. The method comprises commanding, by a control unit, a pressure equipment to set an inner cuff pressure of a cuff at least at a predetermined restricting state pressure; receiving, by the control unit, first arterial oxygen data related to a free-circulation state; receiving, by the control unit, tissue oxygenation data of a tissue of the limb related to the restricting state; receiving, by the control unit, second arterial oxygen data related to the restricting state. The method further comprises determining, by the control unit, a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; applying, by the control unit, an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0014] In a yet further aspect, a controller or computing system comprising a processor configured to perform a method according to any of the examples disclosed herein is provided.

[0015] In a yet further aspect, a computer program comprising instructions, which, when the program is executed by a processor or controller, cause the processor to carry out the method according to any of the examples disclosed herein is provided.

[0016] Advantages derived from these aspects may be similar to those mentioned regarding the first aspect.

[0017] In the present disclosure, the expression "limb" may comprise an arm or a leg.

[0018] In the present disclosure, the terms “system” or “multifunctional system” are used interchangeably.

[0019] In the present disclosure, the terms “cuff” or “inflatable cuff” are used interchangeably.

[0020] In the present disclosure, the expression “tissue oxygenation data” may refer to any kind of data which includes information related to the presence or amount of oxygen in a tissue.

[0021] In the present disclosure, the expression “arterial oxygen data” may refer to any kind of data which includes information related to the level of arterial oxygen, saturation or the amount of oxygen that circulates in an artery.

[0022] In the present disclosure, the arterial oxygen data may comprise arterial oxygen saturation data and / or arterial oxygen content data. The arterial oxygen saturation data may refer to a percentage value. The arterial oxygen content data may refer to an absolute value.

[0023] In the present disclosure, the expression “venous oxygen data” may refer to any kind of data which includes information related to the level of venous oxygen, saturation or the amount of oxygen that circulates in a vein. In the present disclosure, the venous oxygen data may comprise venous oxygen saturation data and / or venous oxygen content data. The venous oxygen saturation data may refer to a percentage value. The venous oxygen content data may refer to an absolute value.

[0024] In the present disclosure, the expression “exercise state or condition” may be related to an exercise at an intensity at least eliciting substantially 100% of the maximal oxygen consumption.

[0025] BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Non-limiting examples of the present disclosure will be described in the following, with reference to the appended drawings, in which:

[0027] Figure 1 schematically illustrates a view of a system according to one example of the present disclosure;

[0028] Figure 2 schematically illustrates a view of the system of Figure 1 on a limb according to one example of the present disclosure;

[0029] Figure 3 schematically illustrates a view of a cuff and a pressure equipment of the system according to one example of the present disclosure;

[0030] Figure 4 schematically illustrates a view of a system according to one example of the present disclosure;

[0031] Figure 5 schematically illustrates a view of a plurality of cuffs and pressure equipment of the system according to one example of the present disclosure;

[0032] Figure 6 schematically illustrates a view of a heat flux sensor of the system according to one example of the present disclosure;

[0033] Figure 7 schematically illustrates a view of a system according to one example of the present disclosure; Figure 8 schematically illustrates a view of a control unit of a system according to one example of the present disclosure;

[0034] Figure 9 is a flow chart schematically illustrating a neural network according to an example of the present disclosure;

[0035] Figure 10 is a flow chart schematically illustrating a convolutional neural network to feed the neural network of Figure 9, according to an example of the present disclosure;

[0036] Figure 11 is a flow chart schematically illustrating a method according to an example of the present disclosure; and

[0037] Figure 12 is a flow chart schematically illustrating a method according to an example of the present disclosure.

[0038] DETAILED DESCRIPTION OF EXAMPLES

[0039] The same reference signs have been used in these Figures to designate matching elements.

[0040] The examples of methods and systems disclosed herein are not constrained to a particular order.

[0041] Figure 1 schematically illustrates a view of a system 100 according to one example of the present disclosure. Figure 2 schematically illustrates a view of the system of Figure 1 on a limb 10 according to one example of the present disclosure. Although Figure 2 illustrates a leg, the limb may be an arm as well.

[0042] As can be seen in the examples of these figures, the multifunctional system 100 for restricting blood flow in the limb 10 comprises an inflatable cuff 110 configured to allow blood flow in the limb 10 at a free-circulation state and to restrict blood flow in the limb at a restricting state. The cuff or pneumatic tourniquet 110 may be placed surrounding the limb as can be seen in Figure 2. The free-circulation state may mean that the cuff does not apply substantially enough pressure over the limb to restrict the blood flow. Therefore, in the free-circulation state, the cuff 110 does not substantially obstruct the blood flow in the limb. The restricting state may mean that the cuff applies enough pressure over or to the limb to substantially restrict the blood flow to at least a certain extent. Therefore, in the restricting state, cuff 110 substantially obstructs the blood flow in the limb.

[0043] System 100 also comprises a pressure equipment 120 in fluid communication with the inflatable cuff 110. The pressure equipment 120 may be configured to set the inflatable cuff 110 at a predetermined pressure. The pressure equipment 120 may feed the cuff 110 with a gas such as air. The pressure equipment 120 may be operated to reduce the pressure inside the cuff 110 as well. In an example, the control unit 150 may be configured to operate or command the pressure equipment 120 to inflate or deflate the cuff 110 a at predetermined rate. The user may enter target pressure and duration values to apply the pressure to the limb. The control unit may be configured to command the pressure equipment 120 and adapt the inflate / deflate rate accordingly.

[0044] Figure 3 schematically illustrates an example of the cuff 110 and a pressure equipment 120. As can be seen in the illustrated example, the cuff 110 comprises an inflatable bladder 111 in fluid communication with the pressure equipment 120. The bladder 111 may be made from plastic material or the like.

[0045] System 100 also comprises a tissue oxygenation sensor 130 configured to gather tissue oxygenation data of a tissue of the limb 10. The tissue of the limb 10 may comprise skeletal muscle.

[0046] The tissue oxygenation sensor 130 may be based on visible light and / or near-infrared spectroscopy or NIRS, for instance, spatially resolved spectroscopy SRS. The tissue oxygenation sensor 130 may include a light source to deliver light to the muscular tissue at least at two different wavelengths in the range of 200 - 1500 nm, for instance, 600 and 1000 nm. The tissue oxygenation sensor 130 may also include at least one light detector to measure the intensity of the exiting light from the tissue. The distance between the light source and the light detector may vary between 3 and 5 cm. From the data retrieved through the tissue oxygenation sensor 130, it may be obtained the oxygen saturation of hemoglobin in the tissue (StCh). The oxygen saturation of hemoglobin in the tissue may be expressed as a percentage.

[0047] In the example of Figure 1 , system 100 comprises an arterial oxygen sensor 140 configured to gather the arterial oxygen data. The arterial oxygen sensor 140 may comprise, for instance, a pulse oximeter or any other sensor that may be capable of measuring the saturation and / or content of the hemoglobin in capillary blood. In some examples, the arterial oxygen sensor 140 may be configured to gather the arterial oxygen saturation data or SpC>2. The arterial oxygen data may be related to the femoral artery and / or the subclavian artery.

[0048] The system 100 comprises a control unit 150 as well. The control unit is configured to:

[0049] - receive first arterial oxygen data related to the free-circulation state. The first arterial oxygen data may be obtained when the cuff allows free-circulation of blood flow in the limb;

[0050] - command the pressure equipment 120 to set an inner cuff pressure at least at a predetermined restricting state pressure. The predetermined restricting state pressure may be defined such that ischemia is induced in the limb 10. The control unit may operate the pressure equipment 120 to set the inner cuff pressure to a value suitable to substantially cause a cessation of blood flow in the limb. The predetermined restricting state pressure may be defined depending on the physiological features of the user or may be an unchanged preset value;

[0051] - receive tissue oxygenation data related to the restricting state. The tissue oxygenation data may be sensed by the tissue oxygenation sensor 130 when the cuff applies sufficient pressure to restrict the blood flow in the limb. The control unit 150 may be also configured to receive tissue oxygenation data in the free-circulation state;

[0052] - receive second arterial oxygen data related to the restricting state. The second arterial oxygen data may be obtained when the cuff applies sufficient pressure over the limb to restrict the blood flow;

[0053] - determine a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value. The control unit 150 may receive tissue oxygenation data at several points in a period, for instance, in at least one cycle of inflation and deflation of the cuff 110. As the blood flow in the limb is restricted in the restricting state, the amount of oxygen in the tissue decreases. The amount of oxygen in the tissue may decrease until stabilizes in the restricting state. The control unit 150 may be configured to determine if a slope between consecutive values of the tissue oxygenation data is equal to or lower than the predetermined slope threshold value. This may mean that the amount of oxygen in the tissue is substantially stable in the restricting state. The control unit 150 may determine the time reference point when the slope between consecutive values of the tissue oxygenation data is equal to or lower than the predetermined slope threshold value;

[0054] - apply an algorithm or first algorithm configured to produce an output related to venous oxygen data of the main vein draining the limb, such as the femoral vein and / or the subclavian vein, and / or their main tributaries. The algorithm is fed with the first arterial oxygen data in the free-circulation state, and the restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point. A value related to the amount of oxygen in the main vein draining the limb may be obtained from the output of the algorithm. This value may be related to the amount of oxygen in the main vein draining the limb or one of its tributaries. The value may be related to an exercise status of a person who is monitored.

[0055] According to an example, a cuff may be placed around a limb of the user. In other examples, cuffs may be placed around the arms and / or legs. That is, from one to four cuffs. The cuff may be in a condition of free circulation of blood flow while the monitored person is exercising. In one example the monitored person may exercise on a cycle ergometer. During exercise or a bout, first arterial oxygen data may be obtained. When the exercise or bout is finished, the control unit may command the pressure equipment to set to the predetermined restrictive state pressure, for example approximately 300 mmHg for a predetermined period, for example approximately 20 seconds. During the restricting state tissue oxygenation data and second arterial oxygen data are obtained. The exercise or bout may have a predetermined duration. The control unit 150 may be configured to receive operation data from the exercise equipment.

[0056] A session of several bouts with a predetermined workload, interspaced by recovery periods including restriction of blood circulation in the limb, may be performed. At each bout, the first arterial oxygen data may be gathered. Second arterial oxygen data and tissue oxygenation data may be gathered while the monitored person has stopped doing the physical activity or is in a post-exercise state. The blood circulation in the limb may be restricted after the bout, for instance after exhaustion. At a restart of a successive bout, the cuff may be deflated to allow circulation substantially fully reestablished.

[0057] In an example, the first arterial oxygen data may be received by the control unit before the pressure equipment is commanded to restrict blood flow. When the blood flow is restricted, then the tissue oxygenation data and the second arterial oxygenation data may be received by the control unit.

[0058] In some examples, the first arterial oxygen data and first tissue oxygenation data may be received by the control unit before the pressure equipment is commanded to restrict blood flow. When the blood flow is restricted, then the second tissue oxygenation data and the second arterial oxygenation data may be received by the control unit.

[0059] The control unit 150 is configured to determine the instant at which tissue oxygenation data decreases with a slope less than a predetermined slope threshold value. At that time a curve or graph representing tissue oxygenation data over time may present a substantially flat shape, whereby a baseline value of tissue oxygenation may be obtained.

[0060] The control unit 150 is configured to apply the algorithm to produce a value related to venous oxygen data of the main vein draining the limb. The inputs to the algorithm include the first arterial oxygen data in the free-circulation state and the restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0061] In some examples, the control unit 150 may be configured to compute a limb oxygen extraction index based on the difference between the first arterial oxygen data and the computed venous oxygen data. The difference may be calculated using values obtained from those data. The limb oxygen extraction index may be determined based on the magnitude of the difference between the first arterial oxygen data and a value of the computed venous oxygen data. The oxygen extraction index may allow to assess an oxygen extraction capacity, for example during exercise. The oxygen extraction capacity may be of interest in fitness, medicine, or rehabilitation.

[0062] In an example, the limb oxygen extraction index may be related to an absolute value or percentage of the O2 supplied to the limb. The O2 extraction may be obtained through the difference between arterial oxygen content CaC>2 and the venous oxygen content, e.g. femoral venous oxygen content CvfC>2 or subclavian venous oxygen content. The control unit 150 may be configured to compute that difference.

[0063] The system may comprise a blood pressure sensor in data communication with the control unit 150 to compute the arterial oxygen tension.

[0064] According to some examples, the system 100 may comprise a plurality of tissue oxygenation sensors 130 to be distributed over the limb 10. Each tissue oxygenation sensor 130 may be in data communication with the control unit 150 through a dedicated channel 135. Channel 135 may comprise a wireless communication and / or a wired communication. The algorithm may be fed with the information received through each channel. Therefore, the accuracy of the output may be improved.

[0065] In some examples, the control unit 150 may be configured to compute values of at least one of oxyhemoglobin and deoxyhemoglobin, total hemoglobin and tissue oxygenation index TOI based on data sensed by the tissue oxygenation sensor 130 and received through each channel 135. The tissue oxygenation index may comprise a tissue oxygen saturation index. The tissue oxygenation data may comprise a tissue oxygen saturation index.

[0066] In some examples, the algorithm may be fed with at least one of the following parameters:

[0067] - limb muscle mass. The limb muscle mass may be obtained through dual photon X-ray absorptiometry, computed tomography, magnetic resonance, bioimpedance, or derived from anthropometric data;

[0068] - anthropometric variables. Some examples of these variables may include weight, height, or body fat percentage;

[0069] - age;

[0070] - gender;

[0071] - oxygen consumption. This parameter may be obtained at rest or in an exercise or effort state of the user;

[0072] - exercise heart rate. This rate may be obtained in an exercise state of the user;

[0073] - resting heart rate;

[0074] - maximum heart rate. This rate may be obtained in an exercise state of the user or estimated.

[0075] As a general rule, the above-listed parameters may be obtained by the control unit 150 in data communication with the dedicated measuring device or introduced through a user interface.

[0076] Figure 4 schematically illustrates a view of system 100 according to one example of the present disclosure. In the example of Figure 4, system 100 comprises a blood flow sensor 160 in data communication with the control unit 150. The blood flow sensor 160 may include a microphone or a Doppler ultrasound sensor. The illustrated example of this Figure also comprises a cuff pressure sensor 112 to sense the pressure inside the cuff 110. The cuff pressure sensor 112 may be in data communication with the control unit 150. It can be envisaged that a system 100 could include the blood flow sensor 160 and / or the cuff pressure sensor 112. When the system comprises the blood flow sensor 160, the control unit 150 may be configured to determine whether the blood flow is restricted in the limb. The control unit 150 may stop inflating the cuff if it is determined that the blood flow is restricted. In other examples of system 100 which is devoid of the blood flow sensor 160, the control unit 150 may be configured to apply the predetermined restricting state pressure which may be sufficient to induce ischemia in the limb.

[0077] Figure 5 schematically illustrates a view of a plurality of cuffs 110 and pressure equipment 120 of the system 100 according to one example of the present disclosure. In this Figure 5 some members of the system 100 have not been illustrated for the sake of clarity. In this example, the system 100 comprises a plurality of cuffs 110, for instance, one cuff per limb, or two cuffs for arms or legs. The control unit 150 may be configured to command the pressure equipment 120 to feed each cuff 110 with gas at a particular pressure. This particular pressure may be a predetermined pressure value. The predetermined pressure value may correspond to the predetermined restricting state pressure. This particular pressure may be the same for all the cuffs 110. However, in some cases, the control unit may be configured to command the pressure equipment 120 to feed each cuff 110 with gas at a different pressure from the rest.

[0078] In some examples of the system, the control unit 150 may be configured to:

[0079] - command the pressure equipment 120 to set the cuff 110 to a predetermined elastic response pressure. The predetermined elastic response pressure may correspond to the predetermined restricting state pressure or a different one;

[0080] - receive cuff pressure data. The cuff pressure data may be sensed by the cuff pressure sensor 112;

[0081] - computing a rate of pressure increase inside the cuff. The rate of pressure increase may refer to an increase of pressure inside the cuff over a period of time. The control unit 150 may receive several values of the pressure inside the cuff over a period of time;

[0082] - determine a muscle elastic response index of the limb based on the pressure increase rate inside the cuff. A stiffer muscle may present a greater resistance against the pressure exerted by the cuff than a softer muscle. Therefore, a stiffer muscle may cause a faster cuff pressure increase while a softer muscle may cause a slower cuff pressure increase. A stiffer muscle may be related to a more powerful muscle than a soft muscle. The elastic response may be determined with the muscles in a relaxed state or with varying degrees of muscle contraction. This may allow analysis of the elastic response of a muscle at rest and under contraction, both under resting conditions of the user or after exercise of the user that may cause varying degrees of fatigue.

[0083] The control unit 150 may be configured to apply an algorithm or elastic index algorithm to produce an output related to the muscle elastic response of the limb. The algorithm may be fed with the rate of pressure increase inside the cuff. The elastic index algorithm may comprise a machine learning algorithm. This machine learning algorithm may comprise a neural network, a convolutional network, recurrent neural networks or any other kind of neural approach. This network may be trained using training rates of pressure increase inside the cuff with an associated muscle elastic response index. The set of training rates of pressure increase inside the cuff may comprise rates of pressure increase inside the cuff obtained, for instance, for:

[0084] - different physiological states of the limb, such as different tissues in the limb apart from the muscular tissue, contour, or diameter of the limb;

[0085] - exercise of the limb, or contraction of the muscle;

[0086] - limb or muscle at rest.

[0087] The elastic index algorithm and the first algorithm may be the same or a different one.

[0088] Figure 6 schematically illustrates a view of a heat flux sensor 170 of system 100 according to one example of the present disclosure. In this Figure 6 some members of system 100 and the exercise equipment have not been illustrated for the sake of clarity.

[0089] The system according to this example comprises a heat flux sensor 170 to be arranged on an area of the skin of the limb. The heat flux sensor 170 may be removably attached to the skin of the monitored person. The control unit 150 may be configured to:

[0090] - receive skin calorimetric data which is related to the heat flux generated by the area of the skin. The skin calorimetric data may be obtained by the heat flux sensor 170;

[0091] - receive power measurement data related to the power produced by the monitored person in an exercise condition. Control Unit 150 may receive data from a produced power sensor 200 attached to the exercise equipment where the monitoring person may be exercising;

[0092] - determine an energy efficiency index by dividing the skin calorimetric data by power measurement data.

[0093] The skin calorimetric data may be sensed at different intensities of effort. The intensity of effort or exercise may be related to the power measured in the exercise equipment driven by the person who is monitored or analyzed. The energy efficiency index may be obtained by measuring the heat flux generated by at least a portion of the limb.

[0094] The energy efficiency index may be defined as a function of the heat flux or flow of energy per unit of skin surface at a given intensity of effort in watts. In other words, the heat flux in watts and the intensity of the effort in watts. As the procedure is based on heat flux, it is not affected by muscle metabolism during exercise.

[0095] This way, indirect calorimetry procedures may be avoided to measure energy efficiency during exercise. Indirect calorimetry can measure the energy efficiency from the mechanical work produced and the expended energy to produce it, wherein the expended energy is calculated from oxygen consumption, using conversion tables. Thus, the indirect calorimetry requires that the exercise is aerobic, i.e., no anaerobic metabolism is involved.

[0096] The energy efficiency index obtained through the present disclosure may make it possible to obtain energy efficiency indices during exercise of any kind.

[0097] System 100 may be used to calculate by back-extrapolation the energy efficiency index at the end of the effort by measuring the heat flux during recovery, i.e. after effort.

[0098] In some examples, the control unit 150 may be configured to determine the heat generated by the area of the skin based on the skin calorimetric data. The heat may be measured over a predetermined area of the skin covered by the heat flux sensor, and even a predefined period of time. Thus, a heat flux generated by the limb, or a portion of the limb may be determined, or even a rate of heat flux in a predefined period of time.

[0099] In the example of Figure 6, the heat flux sensor 170 comprises a frame 171 and a thermopile 172. Frame 171 may comprise a metallic block such as a block made from aluminium. The thermopile 172 comprises a skin portion 173 to be arranged on the skin (not illustrated) and a frame portion 174 to be attached to frame 171. The heat flux sensor 170 comprises a heater 175 and / or a cooler to keep the frame 171 at a predetermined reference temperature. The heater 175 may comprise a resistive heating member or Joule heating member. The cooler may comprise a Peltier cell. The heat flux sensor may comprise a reference or frame temperature sensor 176 in data communication with the control unit 150.

[0100] The thermopile 172 is a thermoelectric component that, by the Seebeck effect, may provide a signal in volts related to the temperature difference between the skin portion 173 and the frame portion 174. This signal in volts may be received by the control unit 150. The heat flow may be calculated as a function of this temperature difference.

[0101] The temperature of frame 171 may be controlled and adjusted to minimize a measuring error of that temperature difference. The heater 175 or the cooler may be actuated by the control unit 150 if the reference temperature gathered by the reference or frame temperature sensor 176 is below or above a predetermined temperature threshold. The predetermined temperature threshold may be room temperature. This may allow the skin heat flow to be measured more accurately.

[0102] Furthermore, system 100 may be used to measure an energy efficiency index of glycolytic metabolism, which is the energy efficiency of glycolysis in the absence of oxygen consumption and phosphocreatine consumption. In order to obtain the energy efficiency index of glycolytic metabolism, the control unit 150 may be configured to record, save or store heat flux data from the limb in a restricting state at the end of a high-intensity effort until exhaustion. The high-intensity effort may be related to supramaximal exercise. Supramaximal exercise may comprise an exercise at an intensity above that eliciting 100% of the maximal oxygen consumption, for instance, 120%.

[0103] During the first 3-5 seconds of occlusion or restriction, residual oxygen trapped in the muscular tissue may substantially disappear. After the 10th second of recovery, there is no more oxygen consumption in the occluded limb, when occlusion is performed in less than 2 seconds up to 300 - 320 mmHg after exhaustion of the user. During occlusion, glycolysis may be still active, and it is possible to measure the heat flux, which may depend on the glycolytic activity present in the muscles and the efficiency of glycolysis. The heat flux may be measured by the system 100 as above detailed. This way, the present system 100 and method 500 may be suitable for obtaining a functional reserve index which is related to the capacity to produce power at the same level or higher than reached at exhaustion. Figure 7 schematically illustrates a view of system 100 according to one example of the present disclosure. Some elements of the system, for instance, tissue oxygenation sensor or arterial oxygenation sensor have not been illustrated for the sake of clarity.

[0104] As can be seen in the example of Figure 7, the pressure equipment 120 comprises:

[0105] - a driving unit 121 to compress a gas to be delivered to the cuff 110. The driving unit may include a compressor;

[0106] - a pressure chamber 122 to receive the compressed gas from the driving unit 121. The pressure chamber 122 may comprise a moisture sensor 123 for control of dew-point and moisture content inside the pressure chamber 122. The moisture sensor 123 may be in data communication with the control unit 150. The control unit 150 may be configured to command a purge valve 124 to purge condensed moisture (not illustrated) in the interior of the pressure chamber if a moisture value inside the pressure chamber is determined to be greater than a predetermined moisture threshold.

[0107] The pressure equipment 120 may also comprise a pressure equipment sensor 125 to sense the pressure of the compressed gas to be fed to the cuff 110. The pressure equipment sensor 125 may be in data communication with the control unit 150.

[0108] The pressure equipment 120 may also comprise a pressure relief valve 126 in fluid communication with the pressure chamber 122.

[0109] The system 100 may comprise a fluid path 300 to fluidly communicate the pressure equipment 120 and the cuff 110.

[0110] The system 100 may comprise a pneumatic regulator 310 arranged in the fluid path 300 between the pressure equipment and the cuff. The pneumatic regulator 310 may allow to keep the pressure of the gas, which is supplied to the cuff, under a predefined value.

[0111] System 100 may comprise a charging element 320 to control or allow the gas flow to be supplied to the cuff 110. The pressure charging element may be arranged downstream of the pneumatic regulator 310, and the charging element may be operable by the control unit 150. The gas flow may be accurately controlled to feed the cuff 110. The charging element 320 may be operated to inflate the cuff 110.

[0112] The system 100 may comprise a discharge element 330 to discharge compressed gas from the cuff 110. The discharge element may be operable by the control unit.

[0113] The discharge element 330 may be operated to deflate the cuff 110.

[0114] In some examples of the system, the control unit 150 may be configured to command the discharge element 330 to discharge compressed gas from the cuff 110 after the restriction period is over.

[0115] According to some examples, the control unit 150 may be configured to:

[0116] - receive operation data of exercise equipment. The control unit 150 may be in data communication with a controller or the like of an exercise equipment where the person is doing exercise. The operation data may comprise at least one of idle or rest status, and operating or exercise status;

[0117] - command the pressure equipment to inflate a cuff during a predetermined restriction period if the exercise equipment is in idle status.

[0118] In some examples of the system, the control unit 150 may be configured to command the pressure equipment 120 to perform a plurality of cycles of inflation and deflation. Features of each cycle of inflation and deflation may vary, e.g. duration, intensity of effort, etc. The control unit 150 may be configured to trigger inflation and / or deflation based on received exercise equipment state data.

[0119] Figure 8 schematically illustrates a view of control unit 150 of a system according to one example of the present disclosure. The control unit 150 may comprise a controller 150. The controller 150 may be a processor, a chip, a computational device, or processing resources that executes sequences of machine-readable instructions contained in a memory. Controller 150 performs operations on data. The memory may be a non-transitory machine-readable storage medium 151. As can be seen in Figure 8, the non-transitory machine-readable storage medium 151 is coupled to the controller 150. Examples of a non-transitory machine-readable storage medium may include a memory device, a floppy disk, a compact disk (CD), a digital versatile disk (DVD), a USB drive, a computer memory, a read-only memory, or other devices that may store computer code. The machine-readable instructions may comprise a computer program(s) in the form of source code, object code, a code intermediate source, and object code such as in partially compiled form, or in any other form suitable for use in implementing the methods according to the present disclosure.

[0120] In one example, the algorithm may comprise a neural network 400, such as an artificial neural network. However, the algorithm may comprise a convolutional network, recurrent neural networks, shallow networks or any other kind of neural approach. Although the example detailed in the following is based on a neural network, the algorithm may comprise other examples of machine learning algorithm, such as a deep learning algorithm, which could be recurrent or not.

[0121] Figure 9 is a flow chart schematically illustrating the neural network 400 according to an example of the present disclosure.

[0122] The neural network 400 of Figure 9 has been schematically illustrated. The number of nodes 410 shown is not limiting and may vary depending on the case.

[0123] In the present disclosure, the neural network 400 is an example of a neural approach.

[0124] In the example of Figure 9, the neural network 400 comprises an input layer 420, a hidden layer 430, and an output layer 440. Although three layers have been depicted, the number of layers of the neural network may vary depending on the case. For instance, the neural network 400 may include two or more hidden layers 430. The use of hidden layers may help to produce significantly accurate outputs that may encompass more scenarios than the set of training inputs.

[0125] The input layer 420 may receive the first arterial oxygen data, and the restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point. The input layer 420 may also receive limb muscle mass, anthropometric variables, age, gender, race, skin color, oxygen consumption, exercise heart rate, resting heart rate, and / or maximum heart rate. The number of inputs may vary depending on the case.

[0126] In Figure 9 there are some connection lines 450 between nodes 410 of the different layers. The connection lines 450 are related to the weights between nodes. Weight may be a parameter that transforms input data within the network's hidden layers. Weight may be a filter or kernel of the neural network.

[0127] The inter-node weights’ values may vary as the neural network 400 is trained.

[0128] The neural network 400 may process the input layer data using connection weights or inter-node weights.

[0129] The output layer 440 may provide at least one numerical value and / or text, associated with the input data. The numerical value and / or text may refer to venous oxygen data of the main vein draining the limb and or one of its tributaries.

[0130] A deep learning or training algorithm may be used to train the machine learning algorithm such as the neural network 400. A large amount of data may be considered to determine venous oxygen data of the main vein draining the limb. The neural network may be trained with first arterial oxygen data, and the restriction arterial oxygen value from the second arterial oxygen data related to different states. The controller 150 may be configured to train the neural network with a set of training first arterial oxygen data, and training restriction arterial oxygen values from the second arterial oxygen data.

[0131] In some examples, the controller 150 may perform a supervised training of a computer- implemented machine learning model, using the set of training first arterial oxygen data, and training restriction arterial oxygen values from the second arterial oxygen data.

[0132] A backpropagation approach may be applied for training the neural network 400. The neural network 400 may be a feedforward neural network, or a deep neural network.

[0133] The neural network may be trained using training first arterial oxygen data, and a training restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point, with an associated venous oxygen data of the main vein label.

[0134] The training first arterial oxygen data, and a training restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point may comprise those data obtained, for instance from a condition as set forth below, or a combination of at least two of them: exercise, post-exercise, and / or resting state; different exercises; different intensities of exercise; different limbs; different limb muscle mass; different anthropometric variables; different ages; different genders; different races; different skin colors; different oxygen consumptions; different exercise heart rates; different resting heart rates; and / or different maximum heart rates.

[0135] The associated venous oxygen data of the main vein associated with training data may comprise outputs with ground truth. The ground-truth outputs may comprise venous oxygenation data obtained from blood samples withdrawn according to at least one of the above listed conditions.

[0136] Figure 10 is a flow chart schematically illustrating a convolutional neural network to feed the neural network of Figure 9, according to an example of the present disclosure;

[0137] The input layer 420 of the neural network 400 may be provided with the output of the convolutional neural network 700. The convolutional neural network 700 may comprise a starting layer 710, a first convolution layer 720, a first reduction or pooling layer 730, a n convolution layer 740, and a n reduction layer 750. The inputs to use in the starting layer 710 may be the same as those used for feeding the neural network 400 of Figure 9. The convolutional neural network 700 may comprise fully connected layers, for instance, included in the neural network 400. Thus, the layers of the neural network may form the last layers of the convolutional neural network 700.

[0138] According to some examples, system 100 may comprise a screen or the like in data communication with the control unit 150 to display an outcome of the control unit. Figure 11 is a flow chart schematically illustrating a method 500 according to an example of the present disclosure. The method 500 comprises:

[0139] - receiving 510, by the control unit, first arterial oxygen data related to a free- circulation state. The first arterial oxygen data may be gathered by the arterial oxygen sensor 140;

[0140] - commanding 520, by the control unit 150, the pressure equipment 120 to set an inner cuff pressure of the cuff 110 at least at a predetermined restricting state pressure;

[0141] - receiving 530, by the control unit 150, tissue oxygenation data of a tissue of the limb related to the restricting state. The tissue oxygenation data may be gathered by the tissue oxygenation sensor 130;

[0142] - receiving 540, by the control unit 150, second arterial oxygen data related to the restricting state. The second arterial oxygen data may be gathered by the arterial oxygen sensor 140;

[0143] - determining 550, by the control unit 150, a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value;

[0144] - applying 560, by the control unit 150, an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0145] The method 500 may be implemented using a system 100 according to any of the examples disclosed herein. The system 100 may be configured to implement a method 500 according to any of the examples disclosed herein.

[0146] Some examples of the present disclosure may allow to perform of blood flow restriction exercises. The exercise may be addressed for several purposes.

[0147] The method 500 may comprise computing, by the control unit 150, a limb oxygen extraction index based on the difference between the first arterial oxygen data and the venous oxygen data.

[0148] The method 500 may comprise interpolating, by the control unit 150, data related to the venous oxygen data of the vein corresponding to arterial oxygen data between the first arterial oxygen data and the second arterial oxygen data. In one example of method 500 and system 100, first arterial oxygen data may be gathered during exercise.

[0149] In one example of the method 500 and the system 100, the second arterial oxygen data and tissue oxygenation data of a tissue may be gathered post-exercise.

[0150] The method 500 may comprise:

[0151] - receiving, by the control unit 150, cuff pressure data;

[0152] - computing, by the control unit 150, a rate of pressure increase inside the cuff;

[0153] - determining, by the control unit 150, a muscle elastic response index of a limb based on the rate of pressure increase inside the cuff.

[0154] According to an example of method 500, when system 100 comprises a heat flux sensor to be arranged on an area of the skin of the limb, the method 500 comprises:

[0155] - receiving, by the control unit 150, skin calorimetric data which is related to the heat flux generated by the area of the skin;

[0156] - receiving, by the control unit 150, power measurement data related to the power produced by the monitored person in an exercise condition;

[0157] - determining, by the control unit 150, an energy efficiency index by dividing the skin calorimetric data by power measurement data.

[0158] In some examples, method 500 may comprise determining, by the control unit 150, the heat generated by the area of the skin based on the skin calorimetric data.

[0159] The method 500 may comprise:

[0160] - receiving, by the control unit 150, operation data of exercise equipment;

[0161] - commanding, by the control unit 150, the pressure equipment to inflate a cuff during a predetermined restriction period if the exercise equipment is in idle status.

[0162] The method 500 may comprise commanding, by the control unit 150, the discharge element to discharge compressed gas from the cuff after the restriction period is over.

[0163] The method 500 may comprise commanding, by the control unit 150, the pressure equipment 120 to perform a plurality of cycles of inflation and deflation. The inflation and / or deflation may be triggered based on received exercise equipment state data.

[0164] In some examples of the method 500, the algorithm or first algorithm may comprise a machine learning algorithm. The algorithm of method 500 may comprise a neural network, a convolutional network, recurrent neural networks or any other kind of neural approach but also other type of algorithms based on machine learning as for example linear and nonlinear regression, Support Vector Machines, Decision Trees, Random Forests, K-Nearest Neighbors, Naive Bayes etc. The algorithm could be also supervised or unsupervised.

[0165] Figure 12 is a flow chart schematically illustrating a method 600 according to an example of the present disclosure. The method 600 of Figure 12 is related to a training method.

[0166] According to a further aspect, a method 600 for training a neural network to be used in a method for operating a multifunctional system for restricting the blood flow of a limb according to any of the examples disclosed herein, is disclosed. The method 600 for training comprises:

[0167] - providing 610 a set of training first arterial oxygen data, and a training restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point;

[0168] - training 620 the neural network with associated venous oxygen data.

[0169] According to a further aspect, a computer-implemented method is disclosed. The computer-implemented method may comprise:

[0170] - receiving, by a control unit, first arterial oxygen data related to a free-circulation state;

[0171] - receiving, by the control unit, tissue oxygenation data related to a restricting state;

[0172] - receiving, by the control unit, second arterial oxygen data related to a restricting state;

[0173] - determining, by the control unit, a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value;

[0174] - applying, by the control unit, an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0175] According to yet a further aspect, a system 100 is disclosed. The system 100 may comprise:

[0176] - a first arterial oxygen receiving unit configured to receive first arterial oxygen data related to a free-circulation state;

[0177] - a tissue oxygenation receiving unit configured to receive tissue oxygenation data related to a restricting state;

[0178] - a second arterial oxygen receiving unit configured to receive second arterial oxygen data related to a restricting state;

[0179] - a determining unit configured to determine a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value;

[0180] - an applying unit configured to apply an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0181] As used herein, the term “module” or “unit” may be understood to refer to software, firmware, hardware and / or various combinations thereof. It is noted that the modules are exemplary. The modules may be combined, integrated, separated, and / or duplicated to support various applications. Also, a function described herein as being performed by a particular module may be performed by one or more other modules and / or by one or more other devices instead of or in addition to the function performed by the described particular module.

[0182] The modules may be implemented across multiple devices, associated or linked to corresponding computer-implemented methods proposed herein, and / or to other components that may be local or remote to one another. Additionally, the modules may be moved from one device and added to another device, and / or may be included in both devices, associated with the corresponding methods proposed herein. Any software implementations may be tangibly embodied in one or more storage media, such as e.g. a memory device, a floppy disk, a compact disk (CD), a digital versatile disk (DVD), or other devices that may store computer code.

[0183] The computer-implemented methods according to the present disclosure may be implemented by computing means, electronic means or a combination thereof. The computing means may be a set of instructions (e.g. a computer program) and then methods may comprise a memory and a processor, embodying said set of instructions stored in the memory and executable by the processor. These instructions may comprise functionality or functionalities to execute corresponding methods such as e.g. the ones described with reference to other figures.

[0184] In case the computer-implemented methods are implemented only by electronic means, a controller of the system may be, for example, a CPLD (Complex Programmable Logic Device), an FPGA (Field Programmable Gate Array) or an ASIC (Application-Specific Integrated Circuit).

[0185] In case the computer-implemented methods are a combination of electronic and computing means, the computing means may be a set of instructions (e.g. a computer program) and the electronic means may be any electronic circuit capable of implementing corresponding steps of the methods proposed herein, such as those described with reference to other figures.

[0186] The computer program(s) may be embodied on a storage medium (for example, a CD- ROM, a DVD, a USB drive, a computer memory or a read-only memory) or carried on a carrier signal (for example, on an electrical or optical carrier signal).

[0187] The computer program(s) may be in the form of source code, object code, a code intermediate source and object code such as in partially compiled form, or in any other form suitable for use in implementing the computer-implemented methods according to present disclosure. The carrier may be any entity or device capable of carrying the computer program(s).

[0188] For example, the carrier may comprise a storage medium, such as a ROM, for example, a CD ROM or a semiconductor ROM, or a magnetic recording medium, for example a hard disk. Further, the carrier may be a transmissible carrier such as an electrical or optical signal, which may be conveyed via electrical or optical cable or by radio or other means.

[0189] When the computer program(s) is / are embodied in a signal that may be conveyed directly by a cable or other device or means, the carrier may be constituted by such cable or other device or means. Alternatively, the carrier may be an integrated circuit in which the computer program(s) is / are embedded, the integrated circuit being adapted for performing, or for use in the performance of, the computer-implemented methods proposed herein. According to a yet further aspect, a controller or control unit 150 is disclosed, the controller may comprise a processor 150 configured to perform the method for operating a multifunctional system for restricting blood flow of a limb according to any of herein disclosed examples.

[0190] According to a yet further aspect, a computer program is disclosed. The computer program may comprise instructions, which, when the program is executed by a controller 150, cause the controller 150 to carry out the method for operating a multifunctional system for restricting the blood flow of a limb according to any of herein disclosed examples.

[0191] The machine-readable instructions may be carried in a storage medium or may be carried in a transmissible carrier such as an electrical or optical signal, which may be conveyed via electrical or optical cable or by radio or other means.

[0192] For reasons of completeness, various aspects of the present disclosure are set out in the following numbered clauses:

[0193] Clause 1. A multifunctional system for restricting blood flow of a limb, comprising: an inflatable cuff configured to allow blood flow in the limb at a free-circulation state and to restrict blood flow in the limb at a restricting state; a pressure equipment in fluid communication with the inflatable cuff; a tissue oxygenation sensor configured to gather tissue oxygenation data of a tissue of the limb; an arterial oxygen sensor configured to gather arterial oxygen data; a control unit configured to: receive first arterial oxygen data related to the free-circulation state; command the pressure equipment to set an inner cuff pressure at least at a predetermined restricting state pressure; receive tissue oxygenation data related to the restricting state; receive second arterial oxygen data related to the restricting state; determine a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; apply an algorithm configured to produce an output related to venous oxygen data of the main vein draining the limb, wherein the algorithm is fed with the first arterial oxygen data, a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point. Clause 2. The system according to clause 1 , wherein the control unit is configured to compute a limb oxygen extraction index based on the difference between the first arterial oxygen data and the computed venous oxygen data.

[0194] Clause 3. The system according to any of clauses 1 - 2, wherein the arterial oxygen sensor comprises a pulse oximeter.

[0195] Clause 4. The system according to any of clauses 1 - 3, wherein the tissue oxygenation sensor is based on visible light and / or near-infrared spectroscopy.

[0196] Clause 5. The system according to any of clauses 1 - 4, comprising a plurality of tissue oxygenation sensors to be distributed over the limb, wherein each tissue oxygenation sensor is in data communication with the control unit through a dedicated channel.

[0197] Clause 6. The system according to any of clauses 1 - 5, wherein the control unit is configured to compute values of oxyhemoglobin and deoxyhemoglobin, total hemoglobin and tissue oxygenation index based on data sensed by the tissue oxygenation sensor.

[0198] Clause 7. The system according to any of clause 6, wherein the tissue oxygenation index comprises a tissue oxygen saturation index.

[0199] Clause 8. The system according to any of clauses 6 - 7, wherein the tissue oxygenation data comprises a tissue oxygen saturation index.

[0200] Clause 9. The system according to any of clauses 1 - 8, wherein the tissue of the limb comprises skeletal muscle.

[0201] Clause 10. The system according to any of clauses 1 - 9, wherein the arterial oxygen data may be related to the femoral artery and / or the subclavian artery.

[0202] Clause 11. The system according to any of clauses 1 - 10, wherein the main vein draining the limb comprises the femoral vein and / or the subclavian vein, and / or at least on their tributaries.

[0203] Clause 12. The system according to any of clauses 1 - 11 , wherein the algorithm is fed with at least one of the following parameters: limb muscle mass, anthropometric variables, age, gender, races, skin color, oxygen consumption, exercise heart rate, resting heart rate, and maximum heart rate.

[0204] Clause 13. The system according to any of clauses 1 - 12, wherein the predetermined restricting state pressure is defined such that ischemia is induced in the limb.

[0205] Clause 14. The system according to any of clauses 1 - 13, comprising: a blood flow sensor in data communication with the control unit.

[0206] Clause 15. The system according to clauses 1 - 14, wherein the blood flow sensor comprises a microphone.

[0207] Clause 16. The system according to any of clauses 1 - 15, comprising: a cuff pressure sensor to sense the pressure inside the cuff, wherein the cuff pressure sensor is in data communication with the control unit.

[0208] Clause 17. The system according to any of clauses 1 - 16, wherein the cuff comprises: an inflatable bladder in fluid communication with the pressure equipment.

[0209] Clause 18. The system according to any of clauses 1 - 17, comprising: a plurality of cuffs; wherein the control unit is configured to: command the pressure equipment to feed each cuff with a gas at a particular pressure.

[0210] Clause 19. The system according to clause 18, wherein the control unit is configured to command the pressure equipment to feed each cuff with gas at a different pressure from the rest.

[0211] Clause 20. The system according to clause 16, wherein the control unit is configured to: command the pressure equipment to set the cuff to a predetermined elastic response pressure; receive cuff pressure data; computing a rate of pressure increase inside the cuff; determine a muscle elastic response index of a limb based on the rate of pressure increase inside the cuff.

[0212] Clause 21 . The system according to any of clauses 1 - 20, comprising: a heat flux sensor to be arranged on an area of the skin of the limb; wherein the control unit is configured to: receive skin calorimetric data which is related to the heat flux generated by the area of the skin; receive power measurement data related to the power produced by the monitored person in an exercise condition; determine an energy efficiency index by dividing the skin calorimetric data by power measurement data.

[0213] Clause 22. The system according to clause 21 , wherein the heat flux sensor comprises a frame and a thermopile, wherein the thermopile comprises a skin portion to be arranged on the skin and a frame portion to be attached to the frame, the heat flux sensor comprising a heater and / or a cooler to keep frame at a predetermined reference temperature.

[0214] Clause 23. The system according to clause 22, wherein the heater comprises a resistive heating member.

[0215] Clause 24. The system according to any of clauses 22 - 23, wherein the heat flux sensor comprises a reference or frame temperature sensor in data communication with the control unit.

[0216] Clause 25. The system according to any of clauses 1 - 24, wherein the pressure equipment comprises: a driving unit to compress the gas to be delivered to the cuff; a pressure chamber to receive the compressed gas from the driving unit; wherein the pressure chamber comprises: a moisture sensor for control of dew-point and moisture content inside the pressure chamber, the moisture sensor being in data communication with the control unit, wherein the control unit is configured to command a purge valve to purge condensed moisture in the interior of the pressure chamber if a moisture value inside the pressure chamber is determined to be greater than a predetermined moisture threshold. Clause 26. The system according to clause 25, wherein the pressure equipment comprises: a pressure equipment sensor to sense the pressure of the compressed gas to be fed to the cuff, wherein the pressure equipment sensor is in data communication with the control unit.

[0217] Clause 27. The system according to any of clauses 25 - 26, wherein the pressure equipment comprises: a pressure relief valve in fluid communication with the pressure chamber.

[0218] Clause 28. The system according to any of clauses 1 - 27, comprising: a fluid path to fluidly communicate the pressure equipment and the cuff.

[0219] Clause 29. The system according to clause 28, comprising: a pneumatic regulator arranged in the fluid path between the pressure equipment and the cuff, such that the pressure of the gas which is supplied to the cuff is kept under a predetermined value.

[0220] Clause 30. The system according to clause 29, comprising: a charging element to control de gas flow to be supplied to the cuff, wherein the pressure charging element is arranged downstream of the pneumatic regulator, wherein the charging element is operable by the control unit.

[0221] Clause 31 . The system according to any of clauses 25 - 30, comprising: a discharge element to discharge compressed gas from the cuff, wherein the discharge element is operable by the control unit.

[0222] Clause 32. The system according to any of clauses 1 - 31 , wherein the control unit is configured to: receive operation data of exercise equipment; command the pressure equipment to inflate a cuff during a predetermined restriction period if the exercise equipment is in idle status.

[0223] Clause 33. The system according to clauses 31 and 32, wherein the control unit is configured to: command the discharge element to discharge compressed gas from the cuff after the restriction period is over. Clause 34. The system according to any of clauses 32 - 33, wherein the control unit is configured to: command the pressure equipment to cause a plurality of cycles of inflation and deflation of the cuff.

[0224] Clause 35. The system according to any of clauses 1 - 34, wherein the algorithm comprises a machine learning algorithm.

[0225] Clause 36. The system according to clause 35, wherein the algorithm comprises a neural network, or a deep neural network.

[0226] Clause 37. The system according to clause 36, wherein the neural network comprises a convolutional neural network.

[0227] Clause 38. The system according to any of clauses 36 - 37, wherein the machine learning algorithm is trained using training first arterial oxygen data, and a training restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point, with associated venous oxygen data.

[0228] Clause 39. The system according to any of clauses 1 - 38, wherein the arterial oxygen data comprises arterial oxygen saturation data.

[0229] Clause 40. The system according to any of clauses 1 - 39, wherein the venous oxygen data comprises venous oxygen saturation data.

[0230] Clause 41 . The system according to any of clauses 1 - 40, wherein the arterial oxygen sensor is configured to gather arterial oxygen saturation data.

[0231] Clause 42. A method for operating a multifunctional system for restricting blood flow of a limb according to any of clauses 1 - 41 , wherein the method comprises: receiving, by the control unit, first arterial oxygen data related to a free circulation state; commanding, by the control unit, the pressure equipment to set an inner cuff pressure at least at a predetermined restricting state pressure; receiving, by the control unit, tissue oxygenation data related to the restricting state; receiving, by the control unit, second arterial oxygen data related to the restricting state; determining, by the control unit, a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; applying, by the control unit, an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0232] Clause 43. The method according to clause 42, comprising: computing, by the control unit, a limb oxygen extraction index based on the difference between the first arterial oxygen data and the venous oxygen data.

[0233] Clause 44. The method according to clause 42, comprising: interpolating, by the control unit, data related to the venous oxygen data of the vein corresponding to arterial oxygen data between a value of the first arterial oxygen data and a value of the second arterial oxygen data.

[0234] Clause 45. The method according to any of clauses 42 - 44, wherein second arterial oxygen data and tissue oxygenation data are gathered post-exercise.

[0235] Clause 46. The method according to any of clauses 42 - 45, wherein the system comprises a cuff pressure sensor, the method comprising: commanding, by the control unit, the pressure equipment to set the cuff to a predetermined elastic response pressure; receiving, by the control unit, cuff pressure data; computing, by the control unit, a rate of pressure increase inside the cuff; determining, by the control unit, a muscle elastic response index of a limb based on the rate of pressure increase inside the cuff.

[0236] Clause 47. The method according to any of clauses 42 - 46, wherein the system comprises a heat flux sensor to be arranged on an area of the skin of the limb; the method comprises: receiving, by the control unit, skin calorimetric data which is related to the heat flux generated by the area of the skin; receiving, by the control unit, power measurement data related to the power produced by the monitored person in an exercise condition; determining, by the control unit, an energy efficiency index by dividing the skin calorimetric data by power measurement data.

[0237] Clause 48. The method according to any of clauses 42 - 47, comprising: receiving, by the control unit, operation data of exercise equipment; commanding, by the control unit, the pressure equipment to inflate a cuff during a predetermined restriction period if the exercise equipment is in idle status.

[0238] Clause 49. The method according to clauses 47 and 48, comprising: commanding, by the control unit, the discharge element to discharge compressed gas from the cuff after the restriction period is over.

[0239] Clause 50. The method according to clauses 48 and 49, comprising: commanding, by the control unit, the pressure equipment to cause a plurality of cycles of inflation and deflation of the cuff.

[0240] Clause 51. The method according to any of clauses 42 - 50, wherein the algorithm comprises a machine learning algorithm.

[0241] Clause 52. The method according to clause 51 , wherein the algorithm comprises a neural network.

[0242] Clause 53. The method according to clause 52, wherein the neural network comprises a convolutional neural network.

[0243] Clause 54. The method according to any of clauses 42 - 53, wherein the arterial oxygen data comprises arterial oxygen saturation data.

[0244] Clause 55. The method according to any of clauses 42 - 54, wherein the venous oxygen data comprises venous oxygen saturation data.

[0245] Clause 56. A method for training a machine learning algorithm to be used in a system according to any of clauses 1 - 41 or a method according to any of clauses 42 - 55, the method for training comprising: providing a set of training first arterial oxygen data, and a set of training restriction arterial oxygen values from the second arterial oxygen data corresponding to the determined time reference point; training the machine learning algorithm with associated venous oxygen data.

[0246] Clause 57. A computer-implemented method, comprising: receiving, by a control unit, first arterial oxygen data related to a free-circulation state; receiving, by the control unit, tissue oxygenation data related to a restricting state; receiving, by the control unit, second arterial oxygen data related to a restricting state; determining, by the control unit, a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; applying, by the control unit, an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0247] Clause 58. A system comprising: a first arterial oxygen receiving unit configured to receive first arterial oxygen data related to a free-circulation state; a tissue oxygenation receiving unit configured to receive tissue oxygenation data related to a restricting state; a second arterial oxygen receiving unit configured to receive second arterial oxygen data related to a restricting state; a determining unit configured to determine a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; an applying unit configured to apply an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

[0248] Clause 59. A controller comprising a processor configured to perform the method of clause 42.

[0249] Clause 60. A computer program comprising instruction, which, when the program is executed by a controller, causes the controller to carry out the method of clause 42. Clause 61. A computer program according to clause 60, embodied on a storage medium or carried on a carrier signal.

[0250] Clause 62. A multifunctional system for restricting blood flow of a limb, comprising: an inflatable cuff configured to allow blood flow in the limb at a free-circulation state and to restrict blood flow in the limb at a restricting state; a pressure equipment in fluid communication with the inflatable cuff; a control unit configured to: command the pressure equipment to set an inner cuff pressure at least at a predetermined restricting state pressure; a driving unit to compress gas to be delivered to the cuff; a pressure chamber to receive the compressed gas from the driving unit.

[0251] Clause 63. The system according to clause 62, wherein the pressure chamber comprises: a moisture sensor for control of dew-point and moisture content inside the pressure chamber, the moisture sensor being in data communication with the control unit, wherein the control unit is configured to command a purge valve to purge condensed moisture in the interior of the pressure chamber if a moisture value inside the pressure chamber is determined to be greater than a predetermined moisture threshold.

[0252] Clause 64. The system according to any of clauses 62 - 63, wherein the pressure equipment comprises: a pressure equipment sensor to sense the pressure of the compressed gas to be fed to the cuff, wherein the pressure equipment sensor is in data communication with the control unit.

[0253] Clause 65. The system according to any of clauses 62 - 64, wherein the pressure equipment comprises: a pressure relief valve in fluid communication with the pressure chamber.

[0254] Clause 66. The system according to any of clauses 62 - 65, comprising: a fluid path to fluidly communicate the pressure equipment and the cuff.

[0255] Clause 67. The system according to clause 66, comprising: a pneumatic regulator arranged in the fluid path between the pressure equipment and the cuff, such that the pressure of the gas which is supplied to the cuff is kept under a predetermined value.

[0256] Clause 68. The system according to clause 67, comprising: a charging element to control de gas flow to be supplied to the cuff, wherein the pressure charging element is arranged downstream of the pneumatic regulator.

[0257] Clause 69. The system according to any of clauses 62 - 68, comprising: a discharge element to discharge compressed gas from the cuff, wherein the discharge element is operable by the control unit.

[0258] Clause 70. A multifunctional system for restricting blood flow of a limb, comprising: an inflatable cuff configured to allow blood flow in the limb at a free-circulation state and to restrict blood flow in the limb at a restricting state; a pressure equipment in fluid communication with the inflatable cuff; a cuff pressure sensor to sense the pressure inside the cuff, wherein the cuff pressure sensor is in data communication with a control unit. wherein the control unit is configured to: command the pressure equipment to set the cuff to a predetermined elastic response pressure; receive cuff pressure data; computing a rate of pressure increase inside the cuff; determine a muscle elastic response index of a limb based on the rate of pressure increase inside the cuff.

[0259] Clause 71. A multifunctional system for restricting blood flow of a limb, comprising: an inflatable cuff configured to allow blood flow in the limb at a free-circulation state and to restrict blood flow in the limb at a restricting state; a pressure equipment in fluid communication with the inflatable cuff; a heat flux sensor to be arranged on an area of the skin of the limb; wherein the control unit is configured to: receive skin calorimetric data which is related to the heat flux generated by the area of the skin; receive power measurement data related to the power produced by the user in an exercise condition; determine an energy efficiency index by dividing the skin calorimetric data by power measurement data.

[0260] Although only a number of examples have been disclosed herein, other alternatives, modifications, uses and / or equivalents thereof are possible. Furthermore, all possible combinations of the described examples are also covered. Thus, the scope of the present disclosure should not be limited by particular examples, but should be determined only by a fair reading of the claims that follow. If reference signs related to drawings are placed in parentheses in a claim, they are solely for attempting to increase the intelligibility of the claim, and shall not be construed as limiting the scope of the claim.

Claims

CLAIMS1 . A multifunctional system for restricting blood flow of a limb, comprising: an inflatable cuff configured to allow blood flow in the limb at a free-circulation state and to restrict blood flow in the limb at a restricting state; a pressure equipment in fluid communication with the inflatable cuff; a tissue oxygenation sensor configured to gather tissue oxygenation data of a tissue of the limb; an arterial oxygen sensor configured to gather arterial oxygen data; a control unit configured to: receive first arterial oxygen data related to the free-circulation state; command the pressure equipment to set an inner cuff pressure at least at a predetermined restricting state pressure; receive tissue oxygenation data related to the restricting state; receive second arterial oxygen data related to the restricting state; determine a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; apply an algorithm configured to produce an output related to venous oxygen data of the main vein draining the limb, wherein the algorithm is fed with the first arterial oxygen data, a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

2. The system according to claim 1 , wherein the control unit is configured to compute a limb oxygen extraction index based on the difference between the first arterial oxygen data and the computed venous oxygen data.

3. The system according to any of claims 1 - 2, wherein the arterial oxygen sensor comprises a pulse oximeter.

4. The system according to any of claims 1 - 3, wherein the tissue oxygenation sensor is based on visible light and / or near-infrared spectroscopy.

5. The system according to any of claims 1 - 4, comprising a plurality of tissue oxygenation sensors to be distributed over the limb, wherein each tissue oxygenation sensor is in data communication with the control unit through a dedicated channel.

6. The system according to any of claims 1 - 5, wherein the control unit is configuredto compute values of oxyhemoglobin and deoxyhemoglobin, total hemoglobin and tissue oxygenation index based on data sensed by the tissue oxygenation sensor.

7. The system according to any of claim 6, wherein the tissue oxygenation index comprises a tissue oxygen saturation index.

8. The system according to any of claims 6 - 7, wherein the tissue oxygenation data comprises a tissue oxygen saturation index.

9. The system according to any of claims 1 - 8, wherein the tissue of the limb comprises skeletal muscle.

10. The system according to any of claims 1 - 9, wherein the arterial oxygen data may be related to the femoral artery and / or the subclavian artery.

11. The system according to any of claims 1 - 10, wherein the main vein draining the limb comprises the femoral vein and / or the subclavian vein, and / or at least on their tributaries.

12. The system according to any of claims 1 - 11 , wherein the algorithm is fed with at least one of the following parameters: limb muscle mass, anthropometric variables, age, gender, races, skin color, oxygen consumption, exercise heart rate, resting heart rate, and maximum heart rate.

13. The system according to any of claims 1 - 12, wherein the predetermined restricting state pressure is defined such that ischemia is induced in the limb.

14. The system according to any of claims 1 - 13, comprising: a blood flow sensor in data communication with the control unit.

15. The system according to claims 1 - 14, wherein the blood flow sensor comprises a microphone.

16. The system according to any of claims 1 - 15, comprising: a cuff pressure sensor to sense the pressure inside the cuff, wherein the cuff pressure sensor is in data communication with the control unit.

17. The system according to any of claims 1 - 16, wherein the cuff comprises: an inflatable bladder in fluid communication with the pressure equipment.

18. The system according to any of claims 1 - 17, comprising: a plurality of cuffs; wherein the control unit is configured to: command the pressure equipment to feed each cuff with a gas at a particular pressure.

19. The system according to claim 18, wherein the control unit is configured to command the pressure equipment to feed each cuff with gas at a different pressure from the rest.

20. The system according to claim 16, wherein the control unit is configured to: command the pressure equipment to set the cuff to a predetermined elastic response pressure; receive cuff pressure data; computing a rate of pressure increase inside the cuff; determine a muscle elastic response index of a limb based on the rate of pressure increase inside the cuff.

21. The system according to any of claims 1 - 20, comprising: a heat flux sensor to be arranged on an area of the skin of the limb; wherein the control unit is configured to: receive skin calorimetric data which is related to the heat flux generated by the area of the skin; receive power measurement data related to the power produced by the monitored person in an exercise condition; determine an energy efficiency index by dividing the skin calorimetric data by power measurement data.

22. The system according to claim 21 , wherein the heat flux sensor comprises a frame and a thermopile, wherein the thermopile comprises a skin portion to be arranged on the skin and a frame portion to be attached to the frame, the heat flux sensor comprising a heater and / or a cooler to keep frame at a predetermined reference temperature.

23. The system according to claim 22, wherein the heater comprises a resistive heating member.

24. The system according to any of claims 22 - 23, wherein the heat flux sensor comprises a reference or frame temperature sensor in data communication with the control unit.

25. The system according to any of claims 1 - 24, wherein the pressure equipment comprises: a driving unit to compress the gas to be delivered to the cuff; a pressure chamber to receive the compressed gas from the driving unit; wherein the pressure chamber comprises: a moisture sensor for control of dew-point and moisture content inside the pressure chamber, the moisture sensor being in data communication with the control unit, wherein the control unit is configured to command a purge valve to purge condensed moisture in the interior of the pressure chamber if a moisture value inside the pressure chamber is determined to be greater than a predetermined moisture threshold.

26. The system according to claim 25, wherein the pressure equipment comprises: a pressure equipment sensor to sense the pressure of the compressed gas to be fed to the cuff, wherein the pressure equipment sensor is in data communication with the control unit.

27. The system according to any of claims 25 - 26, wherein the pressure equipment comprises: a pressure relief valve in fluid communication with the pressure chamber.

28. The system according to any of claims 1 - 27, comprising: a fluid path to fluidly communicate the pressure equipment and the cuff.

29. The system according to claim 28, comprising: a pneumatic regulator arranged in the fluid path between the pressure equipment and the cuff, such that the pressure of the gas which is supplied to the cuff is kept under a predetermined value.

30. The system according to claim 29, comprising:a charging element to control de gas flow to be supplied to the cuff, wherein the pressure charging element is arranged downstream of the pneumatic regulator, wherein the charging element is operable by the control unit.

31. The system according to any of claims 25 - 30, comprising: a discharge element to discharge compressed gas from the cuff, wherein the discharge element is operable by the control unit.

32. The system according to any of claims 1 - 31 , wherein the control unit is configured to: receive operation data of exercise equipment; command the pressure equipment to inflate a cuff during a predetermined restriction period if the exercise equipment is in idle status.

33. The system according to claims 31 and 32, wherein the control unit is configured to: command the discharge element to discharge compressed gas from the cuff after the restriction period is over.

34. The system according to any of claims 32 - 33, wherein the control unit is configured to: command the pressure equipment to cause a plurality of cycles of inflation and deflation of the cuff.

35. The system according to any of claims 1 - 34, wherein the algorithm comprises a machine learning algorithm.

36. The system according to claim 35, wherein the algorithm comprises a neural network, or a deep neural network.

37. The system according to claim 36, wherein the neural network comprises a convolutional neural network.

38. The system according to any of claims 36 - 37, wherein the machine learning algorithm is trained using training first arterial oxygen data, and a training restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point, with associated venous oxygen data.

39. The system according to any of claims 1 - 38, wherein the arterial oxygen data comprises arterial oxygen saturation data.

40. The system according to any of claims 1 - 39, wherein the venous oxygen data comprises venous oxygen saturation data.

41. The system according to any of claims 1 - 40, wherein the arterial oxygen sensor is configured to gather arterial oxygen saturation data.

42. A method for operating a multifunctional system for restricting blood flow of a limb according to any of claims 1 - 41 , wherein the method comprises: receiving, by the control unit, first arterial oxygen data related to a free circulation state; commanding, by the control unit, the pressure equipment to set an inner cuff pressure at least at a predetermined restricting state pressure; receiving, by the control unit, tissue oxygenation data related to the restricting state; receiving, by the control unit, second arterial oxygen data related to the restricting state; determining, by the control unit, a time reference point when values of the tissue oxygenation data decrease with a slope less than a predetermined slope threshold value; applying, by the control unit, an algorithm configured to produce an output related to venous oxygen data of a vein of the limb, wherein the algorithm is fed with the first arterial oxygen data, and a restriction arterial oxygen value from the second arterial oxygen data corresponding to the determined time reference point.

43. The method according to claim 42, comprising: computing, by the control unit, a limb oxygen extraction index based on the difference between the first arterial oxygen data and the venous oxygen data.

44. The method according to claim 42, comprising: interpolating, by the control unit, data related to the venous oxygen data of the vein corresponding to arterial oxygen data between a value of the first arterial oxygen data and a value of the second arterial oxygen data.

45. The method according to any of claims 42 - 44, wherein second arterial oxygen data and tissue oxygenation data are gathered post-exercise.

46. The method according to any of claims 42 - 45, wherein the system comprises a cuff pressure sensor, the method comprising: commanding, by the control unit, the pressure equipment to set the cuff to a predetermined elastic response pressure; receiving, by the control unit, cuff pressure data; computing, by the control unit, a rate of pressure increase inside the cuff; determining, by the control unit, a muscle elastic response index of a limb based on the rate of pressure increase inside the cuff.

47. The method according to any of claims 42 - 46, wherein the system comprises a heat flux sensor to be arranged on an area of the skin of the limb; the method comprises: receiving, by the control unit, skin calorimetric data which is related to the heat flux generated by the area of the skin; receiving, by the control unit, power measurement data related to the power produced by the monitored person in an exercise condition; determining, by the control unit, an energy efficiency index by dividing the skin calorimetric data by power measurement data.

48. The method according to any of claims 42 - 47, comprising: receiving, by the control unit, operation data of exercise equipment; commanding, by the control unit, the pressure equipment to inflate a cuff during a predetermined restriction period if the exercise equipment is in idle status.

49. The method according to claims 47 and 48, comprising: commanding, by the control unit, the discharge element to discharge compressed gas from the cuff after the restriction period is over.

50. The method according to claims 48 and 49, comprising: commanding, by the control unit, the pressure equipment to cause a plurality of cycles of inflation and deflation of the cuff.51 . The method according to any of claims 42 - 50, wherein the algorithm comprises a machine learning algorithm.

52. The method according to claim 51 , wherein the algorithm comprises a neural network.

53. The method according to claim 52, wherein the neural network comprises a convolutional neural network.

54. The method according to any of claims 42 - 53, wherein the arterial oxygen data comprises arterial oxygen saturation data.

55. The method according to any of claims 42 - 54, wherein the venous oxygen data comprises venous oxygen saturation data.

56. A method for training a machine learning algorithm to be used in a system according to any of claims 1 - 41 or a method according to any of claims 42 - 55, the method for training comprising: providing a set of training first arterial oxygen data, and a set of training restriction arterial oxygen values from the second arterial oxygen data corresponding to the determined time reference point; training the machine learning algorithm with associated venous oxygen data.

57. A controller comprising a processor configured to perform the method of claim 42.

58. A computer program comprising instruction, which, when the program is executed by a controller, causes the controller to carry out the method of claim 42.

59. A computer program according to claim 58, embodied on a storage medium or carried on a carrier signal.

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