WO2020083857A1 - Computer-implemented method for ascertaining individual training resources of biological organisms, and corresponding apparatus - Google Patents

Abstract

The present invention relates to a computer-implemented method (10) for ascertaining individual training resources of biological organisms on the basis of a time profile of successive training states and to a corresponding apparatus. The method comprises inputting (15) at least one temporal performance profile and a respective time interval in the starting phase and/or in the end phase of the respective temporal performance profile, which have been ascertained on the basis of execution of a respective prescribed motion sequence by the biological organism with a prescribed form of action and under a respective prescribed load in a current training state; computing (16) a respective mean performance in the respective input time interval in the starting phase and/or in the end phase of the respective temporal performance profile for each input performance profile; and ascertaining (17) a current neuromuscular base variable (Kpot, Akt, Sf) while taking into consideration the respective calculated mean performance and a respective corresponding input previous maximum mean performance in an earlier training state, which permits the current training state to be inferred.

Description

 Computer-implemented method for determining individual training resources of biological organisms and corresponding device

The present invention relates to a computer-implemented method for determining individual training resources of biological organisms on the basis of a time course of successive training states and a corresponding device. The present invention also relates to a computer-implemented method for determining an optimal training focus.

The training capacity, also referred to as training resource, describes the current development resources of a biological system of a biological organism and, in particular, of a person or athlete in connection with sporting activities (hereinafter referred to as training). The training capacity is used to react adaptively to a training stimulus, for example when planning training. The use of biological reserves in order to achieve a positive training effect requires a sufficiently recovered state. In other words, if training resources are insufficient, sporting stress does not lead to the desired effects of training (e.g. improvements in endurance or strength skills). Rather, there can be negative effects in the form of overloads, which in addition to reduced performance can also pose health risks. The training capacity is therefore an essential prerequisite for all areas of athletic and therapeutic training.

In current training and therapy practice, however, there is insufficient awareness of this training capacity and, above all, there are no possibilities to measure it. Usually you train as much as possible. Missing training capacities are usually only noticed when there is a lot of fatigue or overload. It is often overlooked in training practice that the primary task of the biological adaptation mechanisms is, above all, to restore and maintain the physical system and that resources for further increasing performance are only available in a restricted manner. Another important aspect regarding existing training capacities is that they are not available as a global variable, but can be very different depending on the current state within the biological system. For example, there may be a high training capacity in the high-speed range and a low training capacity in the intensive endurance range. In addition to the question of the scope of the Training ("how much?") Therefore also the question of what type of training ("what?") Should be carried out.

This question can be answered very trivially by measuring or recognizing deviations from the training goal (e.g. requirement profile of a certain sport) and then defining them as a development area. However, a general norm profile is assumed and the current person-specific state and individual development potential are not taken into account. Diagnostic approaches such as the lactate performance curve for the endurance area are widespread but primarily designed to delimit training areas and not to recognize the development potential in the individual training areas relative to each other.

US 9,737,758 B1 describes systems for analyzing athletic movements. For this purpose, data for athletes can be recorded using sensors while performing an athletic movement. These sensors can be force plates and the athletic exercise can be a vertical jump that starts on said force plate. From the recorded force-time curves for individual vertical jumps, sections are extracted for different phases of the vertical jumps performed. Using the extracted sections of the force-time curve, an overall concentric vertical pulse, an average eccentric force development rate and an average vertical concentric force are derived.

US 9,886,559 B1 discloses methods and systems for enabling improvements in athlete training and injury management through entropy and third-order spectral analysis of digitized force-time series of movements. A force plate device is used as a biomechanical sensor. In order to be able to manage patient injury management, an approximate entropy and bispectrum are used to check and assess kinetic and kinematic functions. A series of “squat jumps” or counter-movement jumps under conditions that accurately reflect the loads and intensities that characterize sports competitions. Measurements of the time domain variability and disorder, such as sample entropy, approximate entropy, Shannon entropy, etc., are used for the analysis. EP 2 470 076 B1 discloses the analysis of human movements in order to assign a determination of performance in a physical activity domain. To do this, an ordinal or scalar evaluation or an objectively defined discrete classification is used, which is based on a physical ability or physical performance based on measurements taken during the execution of a prescribed movement protocol.

EP 2 263 534 B1 discloses methods and devices for evaluating muscular, physiological parameters such as muscular performance and strength and for creating and updating personalized training programs based on these test results. A series of acceleration values are measured during a series of short movements performed by an athlete. From this, a large number of muscular parameters are calculated and determined on the basis of these training exercises personalized for the athlete. The muscular parameters include muscle strength, extension, reactivity, muscular stiffness and coordination.

At present, the biological abilities or development resources of people are described using various medical parameters that react to stress on the biological system. Separate, very special measurement methods and procedures are required to determine each of these parameters (e.g. creatine kinase or urea analysis from blood serum, lactate lactate measurement, heart rate variability determination, determination of various hormone and inflammation parameters). The problem with this approach is that only an indirect conclusion can be drawn from the measured (physiological) parameters about the current resilience of the biological system. However, all (physiological) parameters currently to be determined are subject to a number of other (health, psychological, etc.) influencing factors and not just the training load alone, which is always accompanied by an error that cannot be estimated.

Furthermore, these methods and procedures aim at a status description relative to an external normative (statistical assessment of laboratory values in relation to the healthy normal population), which does not allow sufficient discriminatory power to assess individual training capacity. The focus of training is currently either based on general norm plans (for certain sports, goals, age groups, etc.), which is very vague and error-prone because the individual requirements are not taken into account, or through diagnostic assessment of individual development potential. The usual sports science approaches are:

(i) the measurement of individual sub-areas (such as, for example, jump test for high-speed force or isometric test for maximum force;

 (ii) the norm-oriented classification of the results (comparison with age groups and the like); and

 (iii) the location of training areas with the greatest deficits.

Specific diagnostic procedures such as For example, a determination of the power deficit via the bilateral deficit, the determination of the muscle performance threshold or the lactate performance diagnostics only provide information for sub-areas of the training and do not allow a comprehensive assessment of development potential.

At present, training plans are also created automatically based on a large amount of data with the help of look-up tables or data mining approaches. A training plan that has already been created is modified after manual entry of updated data. Such methods and procedures are based on “open loop systems”.

The need for a general training capacity has so far only been examined for sub-areas without extensive access. Only from the opposite side - training restrictions due to fatigue influences - are there approaches for determining training capacities. Up to now, however, the current fatigue research in sports and occupational medicine has not been able to develop any meaningful measures that reliably describe complex fatigue. Muscular fatigue is defined as the inability to maintain required or expected performance and is known to be a complex multifactorial phenomenon / problem. There is access to the assessment of muscular fatigue through a drop in athletic performance or through exercise intolerance, whereby these quantities can only be defined and measured for specific applications. This approach is therefore very general and not suitable for differentiated early detection. The medical approaches via metabolic substrates or electromyography are in turn very specifically geared towards the details of muscular fatigue and are usually also very complex in terms of measurement technology.

Surface electromyographic measurements (OEMG) have been used for the qualitative or semi-quantitative determination of the fatigue of individual muscles for many years. Apart from a large measurement variance, OEMG is only able to analyze individual muscles lying on the surface and cannot be extrapolated for fatigue of the entire nerve-muscular system of a biological organism.

The measurement of the heart rate variability (qualitative and quantitative assessment of the cardiac autonomous reaction situation) incorporates not only muscular and nerve parameters, but also numerous other influencing factors and measured variances, so that no reliable conclusions can be drawn about fatigue effects.

However, there is currently no valid methodology for determining individual development potential. Furthermore, open loop systems for training planning are always prone to errors due to the manual input of training data into a system for the automated generation of training plans. In addition to the reliable determination of individual training capacities and development potential, the prerequisite for a “closed-loop system” is a quantitative assessment of the entire training, which represents the controlled variable to be changed in the system. To date, no adequate solutions have been known for this. The strength training is usually recorded via repetitions or series, endurance training via time variables, spec. Training content, such as ski jumping over the number of jumps, etc. However, the scope and intensity of the training cannot be used operationally within a range or for an overall analysis. Furthermore, a "closed loop system" can only work if the setting of the control values is based on a complex, holistic analysis of the biological system and, as already explained, there are currently no solutions for this.

Accordingly, the object of the present invention is a computer

implemented method for determining individual training resources of biological organisms on the basis of a time course of successive training states, and to provide a corresponding device which enables physiologically available results to be quantify the sources of a biological organism, especially a person, directly and without an external normative (i.e. for people compared with at least one other person or in comparison with statistically determined normal values for a certain age of a person) in a simple and comprehensible manner.

Furthermore, it is an object of the present invention to provide a computer-implemented method for determining individual training resources of biological organisms on the basis of a temporal course of successive training states and a corresponding device which make it possible for a biological organism, in particular a person, to be aware of the negative effects of an Protect unbalanced or inappropriate training plans in the form of overload, reduced performance and health risks through adequate training planning based on a few individual or person-specific capacity parameters in a "closed-loop system".

The present invention provides a computer-implemented method for determining individual training resources of biological organisms based on a time course of successive training states according to independent claim 1, a computer-implemented method for determining an optimal training focus according to independent claim 14 and a corresponding computer-based method. implemented device according to independent claim 17.

Advantageous refinements and developments of the present invention are against the dependent subclaims.

According to a first aspect of the present invention, a computer-implemented method for determining individual training resources of biological organisms on the basis of a time course of successive training states comprises the steps: a) entering (15) at least one time performance course (P _{0i t tato} , PmLs _tato ,

P _o LEi _asto , P mi Ei _asto ) and a respective time interval ([t _Sta r _t ; ts _ta r _t + Atp _hase ]; ([t _E n _de -Atp _hase ; t _end ]) in the start phase and / or in the final phase of the respective temporal performance curve (P _o Ls _tato , PmLs _tato , P _o LEi _asto , PmLEi _asto ), which is carried out by the biological organism with a predetermined ac- tion and under a given load in a current training status; b) calculating a respective average power (P _St art_oi_stato, PEnde_oi_stato, Pstart_mi_stato, PEnde_ml_Stat Ps tart ol Ela s _to> Pfinal ol Elasto _·? S tart ml of Elah _to> PEnde_ml Eiasto) in the respective eingege surrounded time interval ([t _Sta rt ; tsim-i + At _{Ph; ls} ]; ([t _En de-Atp _hase ; t _En de]) in the start phase and / or in the end phase of the respective temporal performance curve (P _0i _s _tato , P _mi _s _tato , PoLEiasto , PmLEiasto) for each entered performance curve (PoLstato, PmLstato, Poi Eiasio, R ,,, i riasm; and c) Determine a current neuromuscular base size taking into account the respective calculated mean power (P _S tart_oi_stato, PEnde_oi_stato, Pstart_mi_stato, Pi .nde mi si o, Psian oi ii st _<> Pi .nde oi i, iasi <n Pstart_mi_Eiasto _? PEnde_mi_Eiasto) and a respective corresponding previously entered maximum average power (P _St arcoLstato_max, RE, _K E oi si o „, ax,

P S t ar t ml S tato max PEnde_ ml S t ato max P S tart ol Elas to max PEnde_ ol Elasto max, Pstart ml I laslo max, PEII- de_mi_Eiasto_max) in an earlier training state, which allows conclusions to be drawn about the current training state.

According to a second aspect of the present invention, a computer comprises

Implemented device for determining individual training resources of biological organisms on the basis of a time course of successive training states, which has: an input module that is designed and set up for entering at least one time performance curve (P ₀ i_stato, Pmi _. stato, PoLEiasto, PmLEiasto) and a respective time interval ([t _Sta rt; tstart + ATP _hase]; ([t _en de-at _phase; t _end]) in the starting phase and / or in the end of the respective temporal power profile (P ₀ phase i_stato, Pmi stato, _PoLEiasto. PmLEiasto), which were determined on the basis of the execution of a respective predetermined movement sequence by the biological organism with a predetermined form of action and under a respective predetermined load in a current training state; a calculation module that is designed and set up to calculate a respective average performance ( Pstart_ol_Stato, PEnde_ol_Stato, Pstart_mLSt ato, PEnde_ml_Stato, Pstart_oLElasto, PEnde oLEiasto, Pstait_mi_Eiasto, Pi .nde mi i .Esio) in the time interval entered ([tstaiti ts _tart + Atp _haSe ]; ([t _{En <| L.} -At _{| iaSL} .; t _end ]) in the start phase and / or in the end phase of the respective temporal performance curve (P ₀ i_stato, Pmi _. stato, PoLEiasto, PmLEiasto) for each entered performance curve (Pol Stato, Pml_Stato, PoLEiasto, PmLEiasto) and a determination module that is designed and set up to determine a current neuromuscular base variable (Kpot, Akt , Sf) taking into account the calculated average power (Pstart_ol_Stato, PEnde_ol_Stato, Pstart_mLStato, PEnde_ml_Stato _? Pstart_oLElasto,

P end oi Eias to, Pstait_mi_E sto, Pi .nde mi i .iasm) and a respective corresponding previously entered maximum average power stored in the memory (Pstart_oi_stato_max, REP- de ol Stato max, Pstart mLStato max, Pl nde ml Stato max, Pstart oLElasto max, Pl nde ol I laslo max,

P start_mi_Eiasto_max _? Pi .nde mi i asin max) in an earlier training state, which allows conclusions to be drawn about the current training state.

The computer-implemented method according to the invention and the corresponding computer-implemented device for determining individual training resources of biological organisms on the basis of a time course of successive training states make it possible to quantify the individually available biological training resources of a biological organism, in particular the person-specifically available training resources of a person. The complex or the whole is assumed. The starting point is the measured time performance curve measured in natural, complex movement sequences, such as. B. two-legged jumps, at maximum performance measurement in different resistance areas / loads and in different types of muscular action. This covers a very wide range of stresses in the nerve-muscular system.

The respective neuromuscular basic parameters are determined from the performance curves. Maximum performance measurements with different loads and muscular forms of action generate a continuous performance profile from the low resistance range (corresponds to rapid force) to the high resistance range (maximum force). Regardless of the absolute size of the maximum power, the resistance ranges can be assessed in relation to each other and development potentials can be identified from them, regardless of the norm value.

The starting point is the at least one input performance curve (P _0i stato, Pmi_stato, PoLEiasto, PmLEiasto), which is determined by the biological organism when the specified movement sequence is carried out, as well as the respective time interval ([t _Sta rt; tstart + Atph _aS e]; ([T _~ At _{the end pllaSe} t _{En e])} in the starting phase and / or in the final phase of the respective temporal Leist _li ngs course (Pol Stato, Pml_Stato, PoLElasto, PmLElasto) ·

The biological organism is in particular a human being or an athlete / athlete. The at least one performance curve can also be determined for an animal, such as a horse, which is used for sporting activities. The movement sequence is carried out with a predetermined load or in a predetermined resistance range. In addition, a form of action, statodynamic or elastodynamic, is given for the sequence of movements.

A statodynamic movement sequence takes place from a prestressed (resting) position in which the corresponding muscles of the biological organism are maximally tense. A purely concentric sequence of movements is carried out (direction of movement corresponds to the direction of movement caused by muscle contraction without backward or previous counter movement).

An elastodynamic sequence of movements takes place from a neutral position, in which the corresponding muscles of the biological organism are not tense. First an eccentric movement is carried out up to the prestressed position. The movement is intercepted or slowed down by the muscle tension (direction of movement against the direction of movement caused by the muscle contraction). After that, the same concentric movement as in the statodynamic sequence of movements takes place immediately, without a break in the prestressed position. The biological organism is tested at certain times, for example once a week, in order to determine the current state of training at these times.

From the at least one performance curve

a respective average performance (Pstart_ol_Stato, Pl aidc ol Slalo, Pstart_ml_Stato, Pl aidc ml Slalo,

Psian oi i asioi Pi ide oi i asioi Psiari mi i.iasioi PEnde_mi_Eiasto) in the respective time interval entered ([tstard tstart + Atphase]; ([t _E nde-Atp _hase ; t _Ende ]) in the start phase and / or in the final phase of the respective temporal performance curve (P ₀ i_stato, Pmi _. stato, PoLEiasto, PmLElasto) for each given performance curve (P ₀ i_stato, Pmi _. stato, PoLEiasto, P mi Eiasto). For this purpose, the at least one performance curve in time intervals (Atp _{h; lse)} in the start phase and / or in the end phase of the respective temporal performance curve (P _0i stato, Pmi_stato, PoLEiasto, P mi Eiasto) for each input performance curve (P ₀ i_stato, Pmi _. stato, PoLEiasto,

P mi Eiasto) divided. The temporal distribution of the motion sequence can be carried out uniformly (1/2, 1/3, 1/4, etc.), or it may, for example, ATP _ase = 150 ms [millisecond], given a certain time interval length, or it may be a to limit speed (e.g. v <0.5 m / s [meters per second]) can be specified as the limit for the time interval. Depending on which time interval in the performance course of the movement process with which load and in what form of action is considered, different mean performances (Psian <> i siai <>, Pi ide <> i siai <>, Pstart_mi_stato _? Pi ie mi siai <n Psian oi i asio, Pi aide oi i asioi Psian mi i dasioi PEnde_mi_Eiasto). The mean value of the performance curve in the corresponding time interval is shown as the corresponding mean performance

Psiarl ol Slal Pi aide ol Slal Psiarl ml Slalie Pi aide ml Slal Pstart ol Elasto? Pi aide ol Idasl Psiarl ml Idasl PEII-de_ml idasm).

A current neuromuscular base variable, which allows conclusions to be drawn about the current training status, such as the newly introduced force potential Kpot, activation ability Akt or dielectric strength Sf, is taken into account taking into account the respective calculated average power (Pstart_ol_Statc> ₅ Pi aide ol Slalo, Pstart_ml_Stat ₀₅ Pi aide ml Slalo,

Psian oi i asioi Pi ide oi i asim Pstart_mi_Eiasto _? PEnde_mi_Eiasto) and a respective corresponding previously entered maximum average power (P _St arcoLstato_max, Piaide _< , i siam max,

PS t ar t ml S tato max PEnde_ ml S t ato max PS tart ol Elas to max PEnde_ ol Elasto max _? Pstart ml Idaslo maxs PEII- de_mi_Eiasto_max) determined in an earlier training state.

The current neuromuscular base size allows a quantitative statement about the current state of the muscles and thus the training resources of the biological organism at the current point in time or the time when the predetermined movement sequence is carried out, from which the at least one performance curve originates.

The control device of the device can one or a combination of several data processing devices, such as. B. microcontroller (pC), integrated circuits, application-specific integrated circuits (Application-Specific Integrated Circuit, ASIC), application-specific standard products (Application-Specific Standard Products, ASSP), digital signal processors (DSP), programmable in the field (logic) Gate arrangements (Lield Pro grammable gate arrays, FPGA) and the like. The individual modules of the control device can be implemented as separate and communicatively connected data processing devices or on a single data processing device. The memory of the device can be a data memory such as a magnetic memory (eg magnetic core memory, magnetic tape, magnetic card, magnetic strip, magnetic bubble memory, drum memory, hard disk drive, floppy disk or removable disk), an optical memory (eg holographic memory, optical band, Tesa-Film, Laserdisc, Phasewriter (Phasewriter Du al, PD), Compact Disc (CD), Digital Video Disc (DVD), High Definition DVD (HD DVD), Blu-ray Disc (BD) or Ultra Density Optical ( UDO)), a magneto-optical memory (e.g. MiniDisc or Magneto-Optical Disk (MO disk)), a volatile semiconductor memory (e.g. Random Access Memory (RAM), Dynamic RAM (DRAM) or Static RAM (SRAM)), a non-volatile semiconductor memory (e.g. Read Only Memory (ROM), Programmable ROM (PROM), Erasable PROM (EPROM), Electrically EPROM (EEPROM), Flash-EEPROM (eg USB stick), Ferroelectric RAM (FRAM), magnetoresistive RAM (MRAM) or phase change RAM) or a data carrier or storage medium .

The determination of the basic neuromuscular parameters is possible for all biological organisms that can be used for targeted training and is not restricted to humans (athletes / athletes). Animals, particularly those that are suitable for dressage, such as dogs and horses, can also be analyzed.

The present invention thus creates a computer-implemented method and a corresponding device with which the training state of a biological organism, in particular an athlete / athlete, can be determined individually and quantifiable. Instead of, as with known methods, a physiological parameter (lactate value etc.) and / or a performance value (jump height, maximum weight moved, speed etc.) is compared with reference values and thus only a difference to the desired target value (performance target) is determined According to the present invention, an initial training state or performance of the individual biological organism (athletes / athletes) is measured and then, during training, a renewed measurement is carried out at regular intervals and compared with the previous training conditions / performance values. Thus, an objective training status is determined individually for each biological organism, from which a development potential can be derived. A special feature of the present invention is therefore that no prior knowledge of the biological organism, especially the training person, is necessary. No external criteria, norm values, absolute values or the like are required and any information for the generation of reproducible parameters is obtained from the state or the general condition of the biological organism itself. The current training status of the biological organism (human or athlete / athlete or animal) can thus be determined individually and reliably.

According to a preferred development of the present invention, the following steps are carried out before step a): the biological organism executes at least once the respective predetermined movement sequence with the predetermined form of action and under the respective predetermined load in a current training state;

Measuring a temporal force curve using a force measuring device and / or a temporal acceleration curve using an acceleration measuring device each time the predetermined movement sequence is carried out;

Deriving a respective corresponding temporal speed profile from the respective measured temporal force profile and the body weight of the biological organism;

Deriving from the respective performance curve (P ₀ i_stato, Pmi_stato, PoLEiasto, PmLEiasto) based on the force curve and / or acceleration curves and the respectively determined corresponding temporal speed curve; and

Deriving the respective predetermined time interval ([t _Sta rt; tstart + ATP _hase]; ([t _{hase E} xit-ATP; t _end]) in the starting phase and / or in the final phase of the respective temporal power profile (PoLstato, PmLstato, PoLEiasto, PmLEiasto), such that the respective specified time interval ([ts _tarb ts _tart + Atp _haSe ]) begins in the start phase at a first specified speed (v ₀ ) and the respective specified time interval ([t _end -Atp _ase ; t _end ] ) ends in the final phase at a second predetermined speed (v _max ) and has a respective predetermined time period Atp _{h; lse} . In this way, the at least one neuromuscular base quantity can be determined quasi in real time immediately after the respective predetermined movement sequence has been carried out by the biological organism with the predetermined form of action and under the respective predetermined load in a current training state.

For this purpose, a force measuring plate and / or at least one acceleration sensor can be used.

The biological organism, in particular the athlete / athlete, executes the predetermined movement sequence in at least one predetermined form of action (statodynamic or elastodynamic) with at least one predetermined load (eg 20% or 40% of one's own weight)). In this case, the biological organism can carry out several passes of the predetermined movement sequence in the same predetermined action form and with the same predetermined load, with only the best passage being subsequently analyzed further.

During each execution of the specified movement sequence, the (reactive) forces and / or accelerations occurring are measured with the force measuring device and / or with the acceleration measuring device. In particular, a force plate can be used here. It is essential that no sensors have to be attached or attached directly to the biological organism. The force measuring plate comprises at least one transducer, which converts the occurring forces into a measurable physical quantity. It is particularly preferred to use at least one strain gauge sensor here. The strain gauge sensor converts the occurring forces into corresponding electrical voltages, which result in a measurement signal. The measurement signal can be evaluated by a calculation unit (microcontroller, ASIC, FPGA, computer, etc.) and a corresponding force-time curve can be output or saved. The force plate is placed on a solid surface. The biological organism executes the specified movement sequence in the specified form of action with the specified load on the force measuring plate and the corresponding force-time curve (F (t)) is measured. In an analogous manner, an acceleration-time profile (a (t)) can be measured by the acceleration measuring device (e.g. acceleration sensor in a smartphone, which is attached centrally to the biological organism). For the given sequence of movements, for each given form of action and each given load from the respective force-time curve (F (t)) with the help of the weight (G) of the biological organism in N [Newton] and the corresponding mass (M) of biological organism in kg [kg] the respective acceleration-time curve (a (t)) is calculated, unless this has been determined directly beforehand.

By integrating the acceleration-time curve (a (t)) over time, the corresponding speed-time curve (v (t)) can be calculated.

The speed-time curve (v (t)) can be used to differentiate between the eccentric (negative) movement phase (e.g. bending when jumping), the reversal point (speed is 0) and the concentric (positive) movement phase.

The respective performance curve (P (t) = P ₀ i_stato, Pmi _. Stato, PoLEiasto, PmLEiasto) (power-time curve) can be obtained from the product of the force-time curve (F (t)) and the corresponding speed-time - Course (v (t)) can be calculated.

P (t) = F (t) v (t)

The further calculations and derivations take place in step b). The calculated power curve (P (t)) in the negative phase can be used to control the execution of the movement, whereby the last 150 ms before the reversal point can be used to differentiate between statodynamic and elastodynamic forms of action.

The corresponding path-time curve can be calculated by integrating the speed-time curve. t end

sv (t) dt The corresponding performance curves (P ₀ i_stato, PmLstato, PoLEiasto, PmLEiasto) are derived from the force-time courses and / or acceleration-time courses measured for the different types of action and loads and the further courses calculated from them. The required average performance can be derived from the performance profiles

(Pstart ol Stato _? Pstart ml Stato _? Pstart ol Elasto _? Pstart ml Elasto _? Pl nde ol Slalom Pl nd ml Stator Pl nde ol Idasloi

P end mi Eiasto) can be calculated to calculate the basic neuromuscular parameters. For this purpose, the first time interval ([t _Sta rt; tstart + ATPH _aS e]) or the second time interval _{([t, il | L-ATP. H; ISL;} t _end.]) Of the power traces viewed and in each case the average power calculated .

At least one current neuromuscular base variable is then derived from the performance curves and (stored) previous maximum average powers or forces at the reversal point, as described above.

Based on only one force-time curve or acceleration-time curve and (stored) historical data (maximum values of the average outputs), the current one Training status of a biological organism (athlete / athlete, animal, etc.) individually, whether jective and reliable.

According to a further preferred development of the present invention, in step a) the input of a first performance curve (P _0i stato), which was determined without load on the basis of a statodynamic movement sequence, which takes place from a muscularly preloaded starting position of the athlete in a first direction of movement , and a second power curve (P _m i_stato), which was determined on the basis of the same statodynamic movement sequence with a predetermined load; in step b) calculating a first average power (Pstart_oLstato) from the first power curve (P _0i stato) and a second average power (Pstart_mLstato) from the second power curve (Pmi_stato) in a first time interval ([tstarti tstart + Atp _aS e ]) in the start phase of the respective temporal performance curve (P _0i stato, Pmi_stato), which corresponds to a start phase of a concentric phase of the specified movement sequence; in step c) the determination of a current force potential (Kpot) as a neuromuscular base variable from the first average power (Pstart_oLstato) and the second average power (Pstart mi stato) as well as the respective previous maximum average power

(Pstart ol Stato max, Pstart ml Stato max)

Based on the first performance curve, which was determined during a statodynamic movement sequence performed by the biological organism to be tested (e.g. jump from a crouched starting position (squat jump)) without load (without additional weight), and the second performance curve, the with the same statodynamic movement sequence, however, with a load (specified additional weight), i.e. with a different load, was determined, the correspondingly calculated first and second average power (PstarcoLstato, Pstart mi stato) and their previous maximum values (P _S tar _L oLstato_max,

P start mi stato max) determines the current strength potential (Kpot) of the biological organism.

The strength potential as a neuromuscular base size or muscle physiological size describes the contractile potential or the existing physiological potential (number of recruitable motor units) and the energetic state of the corresponding muscles (catabolic or anabolic metabolism). A drop in the strength potential shows muscular fatigue (catabolic state) or a reduction in the physiologically recruitable motor units. An improvement to an increase in strength or an anabolic state (increased building processes).

The first performance curve (statodynamic movement sequence without load) becomes, for example, the first average performance in the first time interval, namely the start phase (e.g. 150 ms from the start of the concentric movement or time span to speed> = 0.5 m / s), calculated. The second average power in the first time interval, namely the starting phase, is calculated from the second power curve (statodynamic movement sequence with load).

Finally, the force potential of the biological organism is determined from the first average power for the start phase of the statodynamic movement sequence without load and the second average power for the start phase of the stato-dynamic movement sequence with load.

With the strength potential, the training state of the biological organism can be determined objectively and individually.

According to a development of the present invention, the current force potential (Kpot) is determined in step c) according to the following relationship:

To calculate the force potential (Kpot), parameters in the low speed range or in the high resistance range can be used. The average power in the concentric starting phase is particularly suitable for statodynamic movements (e.g. jump) without load (Pstart_oi_stato) and with (additional) load

(Ps tart_ml _Stato)

By the ratio of only two calculated average powers (Pstart_oi_stato,

P start mi stato) with the corresponding previous (historical) maximum mean performance (Pstart oi stato max _? Psi i mi siaio _{m; l} x) can be used for every biological organism (sport ler / athlete, animal, etc.) the current training status in the form of the current strength potential (Kpot) can be individually and objectively reliably and easily quantified.

According to a further preferred development of the present invention, in step a) the or a first performance curve (P _0i stato) is entered, based on a statodynamic movement sequence, which takes place from a muscularly preloaded starting position of the athlete in a first direction of movement without Load was determined, and a third performance curve (P _0i Eiasto), which was determined on the basis of an elastodynamic movement sequence, which occurs from a muscularly relaxed resting position of the athlete in an opposite second movement direction to the starting position as a reversal point and then in the first movement direction, without load ; in step b) calculating the or a first average power (Pstart_oLstato) from the first power curve (P _0i stato) and a third average power (Pstart_oLEiasto) from the third power curve (P _0i Eiasto) in a first time interval ([t _Sta rt; tstart + Atph _aS e]) in the start phase of the respective temporal performance curve (P _0i stato, PoLEiasto), which corresponds to a start phase of the concentric phase of the specified movement sequence; and the calculation of a fifth mean performance (PEnde_oi_stato) from the first performance course (P _0i stato) and a seventh mean performance (PEnde_oLEiasto) from the third performance course (Poi Eiasto) in a second time interval ([tEnde-Atphase; tEnde]) in the end phase of the respective temporal performance curve (P _0i stato, PoLEiasto), which corresponds to an end phase of the concentric phase of the specified movement sequence; in step c) the determination of a current activation ability (Akt) as a neuromuscular base variable from the first mean performance (Pstart_oLstato), the third mean performance (Pstart oi Eiasto), the fifth mean performance (PEnde_oi_stato) and the seventh mean performance (P _{End oi Eiasto} ) as well as the respective previous maximum average performance

(Pstart_ol_Stato_max, Pstart_ol_Elasto_max, PEnde_ol_Stato_max, PEnde_ol_Elasto_max) takes place.

Starting from the first performance curve (P _0i stato), which was determined during a statodynamic movement sequence performed by the biological organism to be tested (jump from a crouched starting position (squat jump)) without load (additional weight), and the third performance curve (P _0i Eiasto), which was determined during an elastodynamic movement sequence carried out by the biological organism to be tested (e.g. jumping from an upright (relaxed) starting position over a crouched position) without load (additional weight), is calculated via the correspondingly calculated first, third, fifth and seventh average power

_ _ Pstart oLEiasto, Pi .nde „ii: i _{; l} sm) and their previous maximum values (Pstart_ol_Stato_max ₅ PEnde_ol_Stato_max ₅ Pstart_ol_Elasto_max _? PEnde_ol_Elasto_max) determines the current activation ability (Akt) of the biological organism.

The activation ability (act) is a neuromuscular base or nerve size and describes the nerve stimulation of the muscles of the biological organism (athlete / athlete, animal, etc.). The activation ability (Akt) describes the ability to activate the muscles via the nervous system, i.e. the recruitment and frequency of motor units in the muscles of the biological organism. The ability to activate (act) is an important stress indicator. Stress reduces the ability to activate (Akt) and increases the regeneration time. On the basis of the activation ability (act) it can also be distinguished, for example, whether the training load was too high or the regeneration time or the regeneration quality was too low.

From the first performance curve (statodynamic movement sequence without load), the first average power in the first time interval, namely the start phase (e.g. 150 ms from the start of the concentric movement or time span to speed> = 0.5 m / s), and the third average power in the second time interval, namely the final phase (e.g.

B. 150 ms to the end of the concentric movement or time period from which the speed is> 80% [percent] of the maximum speed reached (v _max ) is calculated. The fifth average power in the first time interval, namely the start phase, and the seventh average power in the second time interval, namely the end phase, are calculated from the third power curve (elastodynamic movement sequence without load).

Finally, the first mean power becomes the start phase of the statodynamic movement sequence without load, the third mean power to the start phase of the elastodynamic movement sequence without load, the fifth mean power to the end phase of the statodynamic movement sequence without load and the seventh mean power to the end phase of the elastodynamic movement sequence the biological organism's ability to activate is determined without stress. With the activation ability, the nervous training state of the muscles of the biological organism can be determined objectively and individually.

According to a further preferred development of the present invention, the current activation capability (Akt) is determined in step c) in accordance with the following relationship:

To calculate the activation capability, parameters are primarily used that record the output produced in the high speed range or with low resistances. The average power in the concentric final phase is particularly suitable for the elastodynamic movement (jump) without load and for the statodynamic movement (jump) without load. For example, the last 150 ms of the concentric phase can be defined as the final phase or the concentric period in which the movement speed is more than 80% of the maximum speed.

The ratio of the four mean powers (P _S tart_oi_stato,

Pstart_oi_E sto, R _Ep- de oi Eiasto) to their previous (historical) maximum values (P _S tart_oi_stato_max, PEnde_oi_stato_max, Pstart_oi_Eiasto_max, Pi .nde ni i .Esio _{m; l} x) can be used for every biological organism (athlete / athlete, animal, etc. .) the current nervous training state of the muscles in the form of the current activation ability (Akt) can be individually and objectively reliably and easily quantified.

According to a further preferred development of the present invention: in step a) the input of a fourth performance curve (PmLEiasto), which is based on an elastodynamic movement sequence, which from the muscularly relaxed resting position of the athlete in the opposite second movement direction to the starting position as a reversal point and then in the first direction of movement takes place, was determined with a predetermined load; in step a) entering a maximum force (Fu_mi_Eiasto) in the reversal point of the elastodynamic movement sequence; in step b) calculating a fourth average power (Pstart_mi_Eiasto) from the fourth power curve (PmLEiasto) in a first time interval ([tstard tstart + Atphase]) in the start phase of the temporal power curve (Pstart_mi_Eiasto), which is the start phase of the concentric phase corresponds to the given sequence of movements; in step c) the determination of a current tension capacity (Sf) as a neuromuscular base variable from the fourth average power (Pstart_mi_Eiasto) and the entered maximum force (Fu _{mi E} iasto) at the reversal point as well as a previous maximum fourth average power (Pstart_mi_E sto_max) and one maximum previous maximum force (Fu _{mi Eiasto max} ) at the reversal point.

Based on the fourth performance curve (PmLEiasto), which was determined during an elastodynamic movement sequence (jump from an upright (relaxed) starting position over a crouched position) with a load (additional weight) performed by the biological organism to be tested, the correspondingly calculated fourth is used average power (Pstart_mi_Eiasto) and the maximum force at the turning point (F _{U mi} Eiasto) and their previous maximum values (Psi _mI ml i .iasio _{m; l} x, Fu _{mi Eiasto max} ) determined the current elasticity (Sf) of the biological organism .

Tension is a basic neuromuscular size or muscle-physical size and describes the current ability of the muscle / tendon system to absorb mechanical or elastic energy. This ability depends very much on the overall state of recovery. If the amount of training is too high or the rhythm of exercise is incorrect, the tension decreases. This is a protective mechanism to protect the muscles from injuries.

From the fourth performance curve (elastodynamic movement sequence with load), who the fourth average power in the second time interval, namely the start phase (z. B.

150 ms from the start of the concentric movement or time span to speed> = 0.5 m / s), and the maximum force in the reversal point, namely the transition point between eccentric movement and concentric movement (e.g. point at which the downward movement movement to the crouched position is finished and the upward movement to jump when jumping starts as a movement sequence).

Finally, the elasticity of the biological organism is determined from the fourth mean power at the start phase of the elastodynamic movement sequence with load and the maximum force at the reversal point of the elastodynamic movement sequence with load.

With the elasticity, the elastomechanical training state of the muscles of the biological organism can be determined objectively and individually.

According to a further preferred development of the present invention, the current dielectric strength (Sf) is determined in step c) according to the following relationship:

To calculate the tension capacity, performance parameters in the concentric starting phase with the elastodynamic movement sequence (jump) and the maximum force at the reversal point can be used.

By the ratio of the fourth average power (Pstart_mi_Eiasto) and the maximum force (Fu_ _m i_Eiasto) at the point of reversal to their previous (historical) maximum values

(Psim-I ml i iasio _{m; i} x, Fu_mLEiasto_max), the current elastomechanical training state of the muscles in the form of the current tension capacity (Sf) can be reliably and easily quantified individually and objectively for every biological organism (athlete / athlete, animal, etc.) will.

According to a development of the present invention, the method comprises specifying a reference movement sequence with a predetermined path length.

By specifying a movement sequence that uses as many muscle groups of the biological organism as possible (athlete / athlete, animal, etc.), i.e. complex movement sequences such as squat jump or squat jump, rowing, deadlifts, Bench presses, pull-ups, tearing (weight lifting), pushing (weight lifting) etc., but also endurance sports movement sequences such as cycling (on the ergometer), rowing, swimming etc., can be used to determine a particularly precise training state of the muscles of the entire body of the biological organism from the determined performance curves .

According to a further preferred development of the present invention, a respective path covered is determined when executing a respective predetermined movement sequence and an executed movement sequence is only used as valid if the determined path covered of the executed movement sequence is less than a predetermined limit value from the predetermined one Path length of the reference movement sequence deviates.

From the path-time curve (s (t)), the distance covered when executing the specified movement sequence is determined. In order to ensure comparable performance at all times (e.g. during the weekly check of the training status), execution of the specified movement sequence is only considered valid and processed if the distance covered corresponds to the predetermined path or deviates only slightly from it. The predetermined path can be based on a generally predetermined reference movement sequence or an individually determined reference movement sequence, for example when the predetermined movement sequence is initially carried out by the biological organism. For example, in the “jump” movement sequence, a flexed position in which the thighs of the athlete / athlete have an angle of 100 ° [degrees] with respect to the vertical can be used as the starting position for the statodynamic form of action or as a reversal point for the elastodynamic form of action be given. The execution of the movement sequence is validated via the derived path-time curve or the derived path covered.

By looking at the distance covered during the execution of the specified movement sequence for validating the execution, the comparability of the performance curves determined at different times can be ensured reliably and simply.

In this case, a display can be provided on which, with each movement sequence carried out, a respectively determined distance covered and / or information about whether the movement sequence executed is used as valid can be displayed. By displaying the distance covered or the information as to whether the execution of the specified movement sequence is used as valid directly on a screen, the entire process of checking the training status of the biological organism can be carried out in a short time and thus efficiently be performed.

According to a further preferred development of the present invention, the predetermined movement sequence comprises a statodynamic movement sequence in the form of a jump from a squatting position and an elastodynamic movement sequence in the form of a jump from a standing position over the squatting position.

In the case of the statodynamic jump from the crouch position, the biological organism first assumes the crouch position (e.g. angle between the thigh and vertical of 100 °) and holds it for a few seconds and then jumps as high as possible. The hands can remain in the hip or, alternatively, can be pulled up. In the elastic leap over the crouch position, the biological organism first springs into the crouch position from a standing position (eccentric or negative movement) and then reverses the direction of movement when it reaches the crouch position (reversal point) in order to jump off the crouch position as explosively as possible .

The jump from the crouch (squat) or the jumped squat is a very complex movement sequence, in which many muscle groups of the body have to be activated to generate strength but also to stabilize the movement. This results in strengthening processes, from which the training state of the entire musculature, that is to say also in the execution of the jump of muscle groups not directly involved, can be determined very precisely.

According to a further preferred development of the present invention, the method further comprises the step: d) determining a current training capacity (Tkap), which enables a statement about the current training resources of the biological organism (200), taking into account the determined current strength potential (Kpot ) and a previously entered ma- maximum force potential (Kpot _max ) and optionally taking into account the determined current activation ability (Akt) and a previously entered maximum activation ability (Akt _max ) as well as optionally taking into account the determined current tension capacity (Sf) and an entered previous maximum tension capacity (Sf _max ) .

At least the force potential (Kpot) and optionally also the activation ability (Akt) and / or the tension capacity (Sf) are dependent on their change within the recorded time series, i.e. in relation to their respective previous (historical) maximum value (Kpot _max , Akt _max , Sf _max ), to a resultant factor that converts training capacity (Tkap). To calculate the training capacity, all three neuromuscular basic variables, strength potential, activation ability and tension ability, are advantageously calculated into a total factor and viewed over the course of a test series. The contractile potential or the existing physiological potential (number of motor units that can be recruited) and the energetic state of the corresponding muscles (catabolic or anabolic metabolism) flow via the strength potential (Kpot) and, optionally, the ability to contract the muscles via the nervous system activate, via the activation ability (act) and / or the ability of the muscle / tendon system to absorb mechanical or elastic energy via the tension ability (Sf) in the assessment of the current training status of the biological organism (human (athlete / athlete) or Tier) based on the training capacity (Tkap). The training capacity (Tkap) describes in particular the current development resources of the biological organism (person, animal, etc.) in order to react adaptively to a training stimulus. The statement of the training capacity (Tkap) is relative to the individual maximum of the test subject. A reduction in the training capacity (Tkap) means that the biological development resources are limited and the training load should be reduced. Conversely, increasing the training capacity (Tkap) means that the training load can also be increased.

Using the training capacity (Tkap), the time course of the training status and the current development potential of a biological organism can be individually, objectively and reliably quantified and analyzed during training. According to a further preferred development of the present invention, the current training capacity (Tkap) is determined in step d) in accordance with the following relationship:

The contractile potential or the existing physiological potential and the energetic state of the corresponding muscles (strength potential (Kpot)) and the ability to activate the muscles via the nervous system (activation ability (Akt)) and the ability of the Muscle / tendon systems to absorb mechanical or elastic energy (elasticity (Sf)) can be combined.

Due to the ratio of the force potential (Kpot), the activation ability (Akt) and the resilience (Sf) to their previous (historical) maximum values (Kpot _max , Akt _max , Sfmax), for every biological organism (athlete / athlete, animal etc.) the current training status and in particular the current development potential can be determined individually and objectively.

According to a third aspect of the present invention, a computer comprises

Implemented method for determining an optimal training focus of a biological organism, using the method according to the first aspect of the present invention, the steps: e) determining (21) a current training compass value (W), which is between 0 and 180 ° for Determine the optimal training focus, whereby the current training compass value (W) is determined according to the following relationship:

W = St * f _c * 180 ° where f _{c is} a predeterminable gender-specific and / or target-dependent value, which is preferably in the range 7 to 12; where St— (Sts _tato + St _Eiasto ) / 2; Ststato taking into account an entered first performance curve (P _0i stato), which was determined on the basis of a statodynamic movement sequence, which takes place from a muscularly preloaded starting position of the athlete in a first direction of movement, without loading, and an entered second performance curve (P _m i_stato) , which was determined on the basis of the same statodynamic movement sequence with a predetermined load, and the size of the predetermined load is determined; and wherein St _Elasto taking into account an entered third performance curve (P _0i Eiasto), which takes place on the basis of an elastodynamic movement sequence, which occurs from a muscularly relaxed resting position of the athlete in an opposite second movement direction to the starting position as a reversal point and then in the first movement direction Load was determined, and a given fourth performance curve (P _m L _Eiasto which is based on an elastodynamic movement sequence, which takes place from the muscularly relaxed resting position of the athlete in the opposite second movement direction to the start position as a reversal point and then in the first direction of movement a predetermined load was determined, and the size of the predetermined load is determined.

The biological organism to be trained is also considered holistically and as a highly complex nerve-muscle system for calculating individual training areas / training focuses. In step a), the first performance curve (P _0i stato), the second performance curve (Pmi_stato), the third performance curve (P _0i Eiasto) and the fourth performance curve (P mi Eiasto) are entered or previously when the specified movement sequences are carried out determined with the corresponding predetermined forms of action and the corresponding predetermined loads by the biological organism.

Subsequently, for each form of action (statodynamic, elastodynamic) with each load (without additional weight or additionally with additional weight of 20% or 40% of the own weight)) an (absolute) maximum output (P ^max ₀ Lstato, P ^maX mLstato, P ^maX oLEi _as to, P ^maX mLEi _as to) or a relative average power (P ^pos _0i stato, P ^p ° ^S mLstato, P ^p ° ^S oLEi _as to, P ^p ° mLEia _S to).

For better comparability, the respective body weight of the biological organism (M) is also related.

ptnax max {P _ml Stato)

 rml_Stato M

pmax max (P _0i _Eiasto)

 rol_Elasto M

pmax max (P _mi Elasto)

 rml_Elasto M

The gradient of the maximum powers (P ^max ) or the relative mean powers (P ^pos ) between the different loads (L) is then calculated separately for the forms of action.

The mean slope (St) is then calculated from the slopes of the forms of action (St _Stato ,

St _Eiasto ) determined.

Finally, the mean gradient is then converted into an angle between 0 ° and 180 ° with the aid of the predetermined value or factor (f _c ), which can be gender-specific and / or target-dependent and based on empirical values. The value / factor (f _c ) is preferably in the range 7 to 12 (for example 8 for strength athletes or 12 for female endurance athletes).

If e.g. B. the maximum power (P ^max ) in the high resistance range is similar to that in the low resistance range, the current development potential is in the low resistance range. The existing power cannot currently be converted into speed the. Conversely, in the event of a very strong drop in performance over the resistance range, this means that with increasing resistance (L) no additional strength potential can be activated and the primary training goal should therefore be in the high resistance range. The calculated angle or training compass value (W) marks the training focus or the main load range in the training compass. The training compass shows a representation of training areas according to resistance or intensity criteria and can be used for general training categories such as endurance, strength, endurance or specific categories such as B. swimming, etc. can be applied. For strength training, for example, the training compass starts on the left (0 °) with the lowest resistance range for rapid strength training, then continues to the right over the explosive strength range and hypertrophy range up to the maximum strength range (180 °). For endurance, the basic endurance area begins on the left (0 °) and then goes over the transition area and the threshold area to the intensive area on the far right (180 °).

By converting the determined performance curves into a training compass value or angle (W), the current training status regarding the development potential can be represented as very easy to understand. The current training compass value can be shown on the display.

If the training compass value and thus the area in which the development potential of the biological organism (athlete / athlete or animal etc.) is displayed directly on the display, the biological organism (athlete / athlete) and / or its trainer immediately receives a clear feedback about the success of the previous training and the possibilities or optimal direction for the future training.

According to a further preferred development of the present invention, the method further comprises the step: f) specifying training exercises of a training plan which are based on a deviation of a current training _compass value (W) from a predetermined target value (Ws _oii ) from a plurality of predefined training exercises of different loads are determined. The specified target value (W _soii ) is selected, for example, depending on the type of sport (more rapid power or maximum power). Based on the difference (D) between the determined training compass value (W) and the specified target value (W _soii ) (training _goal , e.g. optimal form of competition of an athlete), the training focus is determined by the selection of appropriate exercises. The choice of exercises depends on the one hand on the target value (W _soii ), _{i.e. the final} training _goal , and on the other hand on the difference (D) between the current training compass value (W), i.e. the current training status, and the target value (W _soii ) from. The creation of the training _plan is therefore carried out automatically on the basis of the predetermined training end _goal (target value (W _soii )) and the current training status (training compass value (W)). For this purpose, various exercises based on the target value (W _soii ) and the difference (D) to this are proposed, for example, from a stored list (look-up list). After a certain training period, the performance curves are determined and analyzed again. On the basis of a comparison with previous (maximum) results, the training plan (intensity and / or exercises of the training) is automatically adapted. This is a closed system for training optimization, which enables closed-loop training control.

Thus, a higher quality of training can be guaranteed by reducing subjective influencing factors, but also a wide range of high quality training can be made available. The given training exercises can be shown on the display.

Thus, a determined adjustment of the training plan with regard to the exercises can be implemented immediately by the biological organism or its trainer in a time-saving manner.

According to a development of the present invention, an intensity of the training exercises of the training plan is determined in step f) based on the determined current training capacity (TKap) on the basis of a predetermined quantification system, which is a load parameter for each training category and a factor for each sub-area of the respective training category specifies that sets the intensity in relation to the load parameter of the respective sub-area.

The individually available biological training resources of an organism, in particular the person-specific available training resources, become an individual one Training plan determined and optionally automatically adapted at regular time intervals based on the current training capacity (Tkap) of the biological organism in question, in particular the athlete / athlete concerned. This enables individualized, autonomous control of training in a closed control loop ("closed loop").

For example, value units (WE) can be introduced as a quantification system for the quantitative recording of the control variable “training”. A value unit system can be defined for this. For each training category, a load parameter can be defined for the time being - for example, the number of series for strength or the load time for endurance. A factor can then be defined for each sub-area of the training category, with which the load parameter can be converted into value units (WE). For example, the factor 12 for the high-speed range - which means that 12 series in the high-speed range result in the unit of value 1 (l2 series / factor 12 = 1), or for the endurance basic range the factor 60, which means that 60 minutes of training in the basic area the unit of value is 1 (60 minutes / factor 60 = 1). This value unit system enables the calculated training focus to be assigned to absolute values for any category. This makes it possible to compare loads between different categories and to calculate the total load of the training.

The training plan is therefore created automatically on the basis of the neuromuscular base variables (strength potential (Kpot), tension capacity (Sf), activation capacity (Akt)) and the resulting training capacity (Tkap). After a certain training period, the basic neuromuscular parameters are determined and analyzed again. On the basis of a comparison with previous (maximum) results, the training plan (intensity and / or exercises of the training) is automatically adapted. This is a closed system for training optimization, which enables closed-foop training regulation. Sport training is regulated by regulators of training capacity (Tkap) and load distribution (selection of exercises). The adaptation of the training is made possible by the quantification system (e.g. based on the value unit system). The regulation takes place intraindividually exclusively based on the empirical data of the person. Therefore, at least 2 tests (at different times) are necessary and the reliability increases with the number of measurements. Ideally, tested and scheduled for one week each. The training is then regulated by adjusting the sub-category distribution (selection of exercises) and / or adjusting the total load. For example, if the training capacity (Tkap) drops to a value between 80% and 60%, the total load in training is reduced by 15%.

Thus, a higher quality of training can be guaranteed by reducing subjective influencing factors, but also a wide range of high quality training can be made available. The determined intensity of the training exercises can be shown on the display.

In this way, the biological organism or its trainer can immediately implement a determined adjustment of the training plan with regard to the intensity.

Further features and advantages of the present invention are explained below using embodiments with reference to the figures. It is pointed out that the invention is not to be limited by the embodiments and exemplary embodiments shown. In particular, unless explicitly stated otherwise, it is also possible to extract partial aspects of the facts explained in the figures and to combine them with other components and findings from the present description and / or figures. In particular, it is pointed out that the figures and in particular the proportions shown are only schematic.

Show it:

1 shows a schematic flow diagram of a computer-implemented method for determining individual training resources according to a first embodiment of the present invention;

FIG. 2 shows a schematic illustration of a computer-implemented device for determining individual training resources according to a second embodiment of the present invention; FIG. 3a shows a schematic illustration of a statodynamic jump in embodiments of the present invention;

3b is a schematic representation of an elastodynamic jump in embodiments of the present invention;

4 shows a schematic flowchart of a computer-implemented method for determining an optimal training focus according to a third embodiment of the present invention;

5a is a schematic diagram of the measured and calculated parameter

Statodynamic jump timings without load in embodiments of the present invention;

5b is a schematic diagram of the measured and calculated parameter

Statodynamic jump timings with load in embodiments of the present invention;

6a is a schematic diagram of the measured and calculated parameter

No-load elastodynamic jump timings in embodiments of the present invention;

6b is a schematic diagram of the measured and calculated parameter

Time histories in an elastodynamic jump with load in embodiments of the present invention;

Fig. 7 is a schematic flow diagram of repeated executions of a given motion sequence with a given form of action and under given load in embodiments of the present invention;

Fig. 8 is a schematic flow diagram of the determination and display of the training capacity in embodiments of the present invention; Fig. 9 is a schematic flow diagram of the determination and display of a training plan in embodiments of the present invention;

Fig. 10 is a schematic diagram of the slopes of the maximum powers of the

 Performance curves in embodiments of the present invention;

11 shows a schematic illustration of an exemplary training compass

 Embodiments of the present invention; and

12 shows a schematic illustration of an exemplary determined training plan in embodiments of the present invention.

The same reference numerals designate the same objects, so that explanations from their figures can be used as a supplement.

1 shows a schematic flow diagram of a computer-implemented method for determining individual training resources according to a first embodiment of the present invention.

The method 10 comprises the optional steps: at least one execution 12 of the respective predefined movement sequence by the biological organism 200 with the predefined form of action and under the respective predefined load in a current training state;

Measuring 13 a temporal force curve (F (t)) using a force measuring device and / or a temporal acceleration curve (a (t)) using an acceleration measuring device each time the predetermined movement sequence is carried out;

Deriving a respective corresponding temporal speed profile (v (t)) from the respective measured temporal force profile (F (t)) and the body weight of the biological organism 200; and Deriving 14 from the respective power curve (P _o Ls _tato , P _m Ls _tato , R ,, i Eiasio, R ,,, i Eiasio) based on the force curve (L (t)) and / or acceleration curves (a (t)) as well as the respective determined temporal speed curve (v (t)); and

Deriving 14 of the respective predetermined time interval ([t _Sta r _t; t _Sia, i + ATP _{| iasl} |; ([t _end - ATP _hasei t _end]) in the starting phase and / or in the final phase of the respective temporal power profile (. PoLstato, PmLstato, PoLEiasto, Pmi _. E sto), such that the respective predefined time interval ([ts _tar d ts _tart + Atp _hase ]) begins in the start phase at a first predefined speed (vo) and the respective predefined time interval ( [t] _{, il (| L.} -Atp _{h; ISL} .; t _end ]) ends in the final phase at a second predetermined speed (v _max ) and has a respective predetermined time period Atp _hase .

These steps 11 to 14 are optional, since they do not have to be carried out under real-time conditions, but corresponding data or parameters can be provided in advance with a time delay and can be entered and evaluated at a later time.

In step 15, an inputting erfogt at least one temporal power profile (P _0i stato, PmLstato, PoLEiasto, PmLEiasto) and a respective time interval ([t _Sta rt; t _S tart + ATP _hase]; ([t _En de- Atp _hase; t _end ]) in the start phase and / or in the end phase of the respective temporal performance curve (PoLstato, PmLstato, PoLEiasto, PmLEiasto), which is based on the execution of a respective given movement sequence by the biological organism 200 with a given action form and under a given one Load in a current training state were determined.

In step 16, calculating a respective average power (Pstart_oi_stato, REP de_ol_Stato, Pstart_mLStato, PEnde_ml_Stato, Pstart_oLElasto, PEnde_ol_Elasto, Pstart_mLElasto, PEnde_ml_Elasto) Ml is carried out each specified time interval ([t _S tart + ATP _hase]; ([t _E xit -Atp _hase ; t _En de]) in the start phase and / or in the end phase of the respective temporal performance curve (Poi stato, PmLstato, PoLEiasto, PmLEiasto) for each entered performance curve (P ₀ i_stato, PmLstato,

PoLEiasto, PmLEiasto)

A current neuromuscular base variable Kpot, Akt, Sf is determined in step 17, taking into account the respective calculated average power (Pstart_oi_stato, REP- de_ol_Stato? Pstart_ml_Stato? PEnde_ml_Stato? Pstart_ol_Elasto? PEnde_ol_Elasto? Pstart_ml_Elasto? PEnde_ml_Elasto) And a respective corresponding entered maximum average power

(Pstart ol Stato max? Pl nde ol Stato max Pstart ml Stato max? Pl nde ml Stato max Pstart ol Elasto max? PEII- de_oi_Eiasto_max _? Pstart_mi_Eiasto_max _? PEnde_mi_Eiasto_max) in an earlier training state, which allows conclusions to be drawn about the current training state.

In step 18, which is also optional, a current training capacity Tkap is determined, which enables a statement to be made about the current training resources of the biological organism 200, taking into account the determined current force potential Kpot and an entered previous maximum force potential Kpot _max, and optionally taking into account the determined current activation ability Akt and an entered maximum activation capacity Akt _max and optionally taking into account the determined current voltage capability Sf and an entered previous _maximum voltage capability Sf _max .

When specifying 11 the sequence of movements, a jump from a squatting position (jump squat, “squat jump”) can be specified here. Alternatively, other complex movements can also be specified (rowing, deadlifts, bench press, pull-ups, tearing, pushing, cycling, swimming, running, etc.). Two types of action can be specified, a staodynamic version and an elastodynamic version of the jump from the squatting position. In addition, two loads can be specified, a version without load (without additional weight) load and a version with load (additional weight of e.g. 40% or 20% of your own body weight) of an athlete or another biological organism.

The athlete or athlete can execute the jump in succession 12 as a statodynamic jump without load, as a statodynamic jump with load, as an elastodynamic jump without load and as an elastodynamic jump with load. For each type of action, several runs can be carried out with each load and only the best run in each case, i.e. the run in which the greatest performance was achieved, can be used for the following considerations.

While the athlete is performing the jumps, the time course of the (reactive) forces (force) occurring during the individual executions of the jumps can be measured during measurement 13. Time course, F (t)) can be measured with a force measuring device. Alternatively or additionally, the time course of the accelerations occurring (acceleration-time course, a (t)) can be measured when the individual jumps are carried out (directly on the athlete / biological organism).

Subsequently, when deriving 14 from the measured force curves, temporal power curves (PoLstato, PmLstato, PoLEiasto, PmLEiasto) can be calculated for the jumps with the respective forms of action and loads. For this purpose, a speed-time profile v (t) can be calculated from the force-time profiles F (t) with the weight G of the athlete in N and the mass M of the athlete in kg.

A start time (t _start ) of the jump is the time before the concentric movement phase at which the speed v ₀ is 0 (start position in the squat position for the statodynamic jump and reversal point for the elastodynamic jump). An end time (t _{en le} ) of the jump is the time at which the speed v _{max is} maximum. Thus, integration can initially take place over the entire measured time range and then the time range from the start time to the end time of the jump can be cut out or viewed in isolation.

Based on the respective speed-time curves v (t), an eccentric (negative) movement phase (bending up to the crouch position when jumping), a reversal point (speed is 0) and a concentric (positive) movement phase (crouch position until the jump) be distinguished.

The respective performance curve (P (t) = P ₀ i_stato, Pmi _. Stato, PoLEiasto, PmLEiasto) (performance-time profile) for the jumps with the two forms of action and the two loads can be derived from the product of the respective force-time profile F (t) and the corresponding speed-time profile v (t) can be calculated.

P (t) = F (t) v (t) The calculated power curve P (t) in the eccentric / negative movement phase can be used to control the movement execution, for example the last 150 ms before the reversal point can be used to differentiate between statodynamic and elastodynamic forms of action. Thus, from the force-time profiles L (t) (and / or the acceleration-time profiles a (t)) measured for the different types of action and loads and the further profiles calculated from them, the corresponding power profiles, the first power profile ( P _0i stato) for the statodynamic jump without load, the second performance curve (P _mi stato) for the statodynamic jump with load (e.g. 40% of the body weight of the athlete), the third performance curve (P _0i Eiasto) for the elastodynamic jump without load and the fourth performance curve (PmLEiasto) for the elastodynamic jump with load can be derived.

When entering 15, the first to fourth performance curve (P _0i stato, Pmi_stato, PoLEiasto, PmLEiasto) for the jump with the respective form of action (statodynamic or elastodynamic) and the respective load (without load or with an additional 40% of the body weight of the athlete as a burden) for further analysis. For example, performance profiles can be determined in a training center and then transmitted to an evaluation center for further analysis, where they can be entered and analyzed.

From the power curves (P _{0 i_stato.} Stato Pmi, PoLEiasto, PmLEiasto) are in calculating average outputs 16 (Pstart_oLStato, Pstart_mLStato, Pstart_oLElasto, Pstart_mLElasto, PEnde_ol_Stato, PEII- de mLstato, Pi. _Nde "ii .iasio, Ri ,, kΐo mi i .Esio) for the subsequent determination of neuromuscular base sizes. For this purpose, a first time interval ([ts _tar d ts _tart + Atp _haSe ]) or a second time interval ([t _{], il (| L.} -Atp _{h; I SL} .; T _En de]) of the power curves is considered and in each case the The average power is calculated from the start time (tstart) to the end of a start phase (ts _ta n + atp _hase ) of the jump or from the start of an end phase (t _end -atp _hase ) of the jump to the end time (t _end ) of the jump The start phase and the end phase (Atp _{h; l se} ) of the jump are, for example, each 150 ms long.

First average performance: in the start phase of the statodynamic jump without load:

Second average performance: in the start phase of the statodynamic jump with load:

Third average performance: in the start phase of the elastodynamic jump without load:

Fourth average performance: in the start phase of the elastodynamic jump with load:

Fifth average performance: in the final phase of the statodynamic jump without load:

Optional sixth average power: in the final phase of the statodynamic jump with load:

Seventh average performance: in the final phase of the elastodynamic jump without load:

Optional eighth average power in the final phase of the elastodynamic jump with load:

A corresponding path-time profile s (t) is calculated by integrating the speed-time profile v (t) from the start time (ts _ta rt) to the end time (tEnd) of the jump.

In addition, a maximum force (L _{u mi Eiasto} ) at the reversal point of the elastodynamic jump with load (from the corresponding force-time curve (L (t)) is determined.

From the path-time profiles s (t) of the jumps with the different forms of action and the different loads, a respective path covered is determined. An executed jump (and its performance curve) is only used as valid if the determined distance covered deviates from a predetermined path of an associated reference movement sequence (reference jump) by less than a predetermined limit value. In order to ensure comparable performance curves at all times (e.g. during the weekly check of the training status), execution of the specified movement sequence is only considered valid and the associated performance curve processed if the distance covered corresponds to the predetermined path or only slightly (preferably less than 5%) deviates from this. For the given jump, the squat position, in which the thighs of the athlete / athlete have an angle of 100 ° with respect to the vertical, is given as the starting position for the statodynamic form of action or as the reversal point for the elastodynamic form of action. The execution of the movement sequence is thus validated via the derived path-time profile s (t) or the derived path covered.

FROM the mean performance (Pstart_ol_Statc> ₅ Pstart_ml_Stat0 ₅ Pstart_ol_Elastc> ₅ Pstart_ml_Elast0 ₅ PEnde_ol_Stato _? P Ende mi stato _? Pi .nde oi i .iasio, Pi .nde mi i .iasio) and previous (saved) maximum mean

Services (Pstart_ol_Stato_max ₅ Pstart_ml_Stato_max _? Pstart_ol_Elasto_max _? Pstart_ml_Elasto_max _? PEnde_ol_Stato_max _?

Pi .nde mi siaio maxi Pi .nde oi i .iasio maxi PEnde_mi_Eiasto_max) are then 17 when they are determined the current neuromuscular base variables force potential Kpot, activation capacity Akt and tension capacity Sf are determined.

The athlete's current force potential Kpot is calculated from the ratio of the first average power (Pstart_oi_stato) to the start phase of the statodynamic jump without load and the second average power (Pstart_mi_stato) to the start phase of the statodynamic jump with load to the corresponding previous maximum average power

 (Pstart_ol_Stato_max Pstart_ml_Stato_max) determined. "- 0.5

The athlete's current activation ability Akt is calculated from the ratio of the first mean performance (Pstart_oi_stato) to the start phase of the statodynamic jump without load, the third mean performance (Pstart_oi_Eiasto) to the start phase of the statodynamic jump without load, the fifth mean performance (PEnde_oi_stato) to the end phase the statodynamic jump without load and the seventh mean power (PEnde_oi_Eiasto) at the end phase of the elastodynamic jump without load at the corresponding previous maximum mean powers (Pstart_ol_Stato_max _? Pstart_ol_Elasto_max _? PEnde_ol_Stato_max _? PEnde_ol_Elasto_max).

The athlete's current resilience Sf is calculated from the ratio of the fourth mean power (Pstart_mi_Eiasto) to the start phase of the elastodynamic jump with load and the maximum force (F _{u ml E asto} ) at the reversal point of the elastodynamic jump with load to the previous maximum fourth mean Power (Pstart_mi_Eiasto_max) and the previous maximum force (F _u _ _mi _Eiasto_max) determined at the reversal point.

When determining 18, a current training capacity Tkap of the athlete can be determined from the ratio of the current force potential Kpot, the current activation ability Akt and the current tension capacity Sf of the athlete to corresponding previous (stored) maximum neuromuscular base variables (Kpot _max , Akt _max , Sf _max ) will.

Fig. 2 shows a schematic representation of a computer-implemented device for determining individual training resources according to a second embodiment of the present invention.

The device 100 comprises a control device 101 in the form of a computer with integrated memory 102 (hard disk and portable storage medium) and display 104 and a force measuring plate 103.

The control device 101 is designed and set up to carry out the steps of the method according to FIG. 1, with or without the optional steps 11 to 14 and 18 being included.

The force-time profiles are measured using the force measuring plate 103, the athlete to be examined performing the jumps with the two different forms of action and the two different loads on the force measuring plate 103. After each execution of the jump, the distance covered and information about whether the jump was considered valid are shown on the display 104. In addition, the determined current force potential Kpot, the determined current activation ability Akt and the determined current tension ability Sf as well as the determined current training capacity Tkap of the athlete are shown on the display 104.

3a is a schematic representation of a statodynamic jump in embodiments of the present invention, and FIG. 3b is a schematic representation of an elastodynamic jump in embodiments of the present invention.

According to FIG. 3a, statodynamic jump is carried out in such a way that an athlete 200 starting from the squatting position as the starting position (concentric movement phase) is as high as jumps off the force plate 103. The starting position is, for example, a squat position in which the thighs of the athlete 200 assume an angle of 100 ° with respect to the vertical. The arms can be pulled over the head during the jump or remain in the hip.

According to FIG. 3b, an elastodynamic jump is carried out in such a way that an athlete 200 moves eccentrically from a standing starting position into the squatting position (e.g. angle between the thigh and vertical of 100 °) and immediately from the squatting position (reversal point of the movement) from the force measuring plate 103 jumps off (concentric movement phase). The arms can be pulled over the head during the jump or remain in the hip.

4 is a schematic flow diagram of a computer-implemented method for determining an optimal training focus according to a third embodiment of the present invention;

The method 20 includes at least steps 15 to 18 of the method 10 according to FIG. 1 and further comprises determining 21 a current training compass value and specifying 22 training exercises for a training plan.

When determining 21, an (absolute) maximum power (P ^max _0i stato, P ^maX mLstato, P ^maX oLEiasto, P ^maX mLEia _S to) is (for each action form (statodynamic, elastodynamic) with each load (without load, with load)) (or alternatively a relative mean power (P ^pos ₀ Lstato,

determined. For better comparability, the respective body weight of the athlete M in kg is also related.

Then increase the maximum performance (P ^max ) (or alternatively the relative mean performance (P ^pos )) between the different loads (L = 100% (body weight of the athlete without load) and L = 140% (body weight of the athlete and additional 40% of this as a load)) for the forms of action (statodynamic and elastodynamic) calculated separately.

The mean slope St is then calculated from the slopes of the forms of action (Sts _tato ,

St _Eiasto ) determined.

Finally, the current training compass value W, which is between 0 and 180 °, for determining the optimal training center is determined.

W = St f _c 180

The factor f _{c is} a predeterminable gender-specific and / or target-dependent value, which is preferably in the range 7 to 12 and is based on empirical values. A difference D is then calculated between a predetermined target value W _soii , which corresponds to an end-of-training _goal and is selected, for example, depending on the type of sport (more rapid strength or maximum strength), and the current training compass value W. Based on the difference D, the training focus is determined by the selection of appropriate exercises from a look-up list for a training plan TP. The choice of exercises depends on the one hand on the target value W _soii , _i.e. the end of training goal (e.g. form of competition), and on the other hand on the difference D between the current training _compass value W, _i.e. the current training state, and the target value W _soii .

Finally, an intensity of the training exercises of the training plan TP is determined on the basis of the determined current training capacity Tkap using a predetermined quantification system. Value units WE are introduced in a value unit system for the quantitative recording of the control variable “training”. A load parameter is initially defined for each training category - for example, the number of series for strength or the load time for endurance. A factor is then defined for each sub-area of the training category, with which the load parameters are converted into the value units WE. For example, the factor 12 for the high-speed range - which means that 12 series in the high-speed range result in the unit of value 1 (l2 series / factor 12 = 1), or for the endurance basic range the factor 60, which means that 60 minutes of training in the basic range result in unit of value 1 (60 minutes / factor 60 = 1). This value unit system enables the calculated training focus to be transferred to absolute values for any category. This makes it possible to compare loads between different categories and to calculate a total load of the training.

After a certain training period, the basic neuromuscular parameters are determined and analyzed again. The training plan (intensity and / or exercises of the training) is automatically adapted on the basis of a comparison with previous (maximum) results. This is a closed system for training optimization, which enables closed-foop training regulation. Sport training is regulated by regulating the training capacity Tkap and the load distribution (selection of exercises). The adaptation of the training is made possible by the quantification system (e.g. based on the value unit system). The regulation is made intra-individually based on the empirical data of the person. That's why at least 2 tests (at different times) and the reliability increases with the number of measurements. Ideally, tests can be carried out weekly and planned for one week at a time. The training is then regulated by adjusting the sub-category distribution (selection of exercises) and / or adjusting the total load. For example, if the training capacity (Tkap) drops by 5%, the total load in training is reduced by 5%.

The control device 101 of the device 100 according to FIG. 2 is also designed and set up, for example, to carry out the steps 21 and 22 of the method 20. The training _compass with the current training _compass value W and the desired value W _soii as well as the training _plan TP with the selected exercises and intensities can be shown on the display 104.

FIG. 5a is a schematic diagram of the measured and calculated parameter-time profiles for a statodynamic jump without load in embodiments of the present invention.

The power curve P (t) (here P _0i stato) is calculated from the force-time curve F (t) with the speed-time curve v (t) calculated by integration. In addition, the distance-time profile s (t) is calculated from the speed-time profile v (t) by integration. As the start time point t _Sta rt is the time at the start of, concentric movement phase defined, to which the velocity v ₀ equal to 0 (before then the speed increases in the positive direction) of the concentric movement phase. The time at which the speed V _{max has reached} its maximum value is defined as the end time t _{end of} the concentric movement phase. Starting from the start time t _Start , for example, the next l50ms (= Atp _hase ) are defined as the start phase [ts _tar d ts _tart + Atp _haSe ]. Analogously, for example, the last 150 ms (= ATP _hare ) before the end time t _{end are} considered the _end phase [t _end- ATP _hare ; t _end ].

With the statodynamic jump without load, the measured (reactive) force F (t) initially increases at the beginning of the concentric movement phase in the start phase [ts _tarti ts _tart + Atp _haSe ], then remains largely constant initially and finally falls in the final phase [t _End - at _phase ; end] again. Accordingly, the velocity v (t) from the start time t _Sta rt rises to end time t _En de an almost linear. The distance covered increases from the start time to beyond the end point (flight phase) before the athlete lands on the floor or the force plate again. The power P (t) increases from the start time to shortly before the end time and is still positive at the end time.

5b is a schematic diagram of the measured and calculated parameter-time profiles in a statodynamic jump with load in embodiments of the present invention. In order to avoid repetitions, only the differences from the courses from FIG. 5 a are described below.

The increase in the force-time curve F (t) is significantly smaller for the statodynamic jump with load in the start phase than for the statodynamic jump without load. Accordingly, in comparison, the speed-time profile v (t) and the path-time profile s (t) also have lower maximum values, in contrast to the unloaded implementation. Since the entire movement sequence is slower than without load, the performance curve P (t) (here P _m Ls _tato ) is somewhat wider and the maximum performance is somewhat lower.

FIG. 6a is a schematic diagram of the measured and calculated parameter-time profiles for an elastodynamic jump without load in embodiments of the present invention. In order to avoid repetitions, only the differences from the courses from FIG. 5 a are described below.

Compared to the two statodynamic jumps, the elastodynamic jumps before the start time ts _{tart of} the concentric movement _{phase have} a decreasing force-time curve F (t) when deflected (eccentric movement _phase ) into the squatting position. This results in a negative speed-time curve before the start time, which changes to positive at speed v ₀ at the start time. Similarly, for the power curve P (t) (here P _0i Eiasto) there is initially a negative curve, which then also _passes through zero at the start time of the concentric movement _{phase with a} subsequent change to positive. The power profile P (t) is in the elastodynamic jump without load in the initial phase [t _Sta rt; tstart + Atph _aS e] somewhat steeper than with the statodynamic jump without load. The measured force-time curve rises sharply even before the start of the concentric movement phase during the eccentric movement phase and then runs approximately constant until the end phase [t _end- ATP _hase ; t _end ] of the concentric movement phase. The path-time curve s (t) is therefore correspondingly initially negative until a negative maximum in the crouch position, i.e. the reversal point of the movement sequence, is reached at the start time of the concentric movement phase, after which the path-time curve s (t) proceeds positively to beyond the end time of the concentric movement phase (flight phase), before the athlete lands on the force plate again.

FIG. 6b is a schematic diagram of the measured and calculated parameter-time profiles for an elastodynamic jump with load in embodiments of the present invention. In order to avoid repetitions, only the differences from the courses from FIG. 5 a are described below.

The force-time curve F (t), the speed-time curve v (t), the performance curve P (t) (here Eiasto) and the path-time curve are similar to the corresponding curves of the elastic jump without Stress, however, the courses are wider and flatter because the movement is slower.

FIG. 7 is a schematic flow diagram of repeated executions of a given movement sequence with a given action form and under a given load in embodiments of the present invention.

When executing 12 the jump in a form of action (statodynamic or elastodynamic) with a load (without load or with load) and simultaneous measurement 13, the corresponding jump can be carried out and measured several times (n times).

Four steps of performing and measuring multiple times are shown here, performing and measuring 13.1 the statodynamic jump without load several times, performing and measuring 13.2 the statodynamic jump with load repeatedly, performing and measuring 13.3 the elastodynamic jump without load and multiple times Carrying out and measuring 13.4 of the elastodynamic jump with load represents Darge. It can be carried out (n times) and measured in succession (with recovery breaks in between) until there is no improvement in the achieved performance or the athlete thinks that they cannot achieve any improvement. After a performance Checking and measuring checks whether the jump made is valid or not. Alternatively, a repetition number n can also be specified.

After a jump has been carried out and measured, the distance covered (determined from the path-time profile s (t)) is used to determine whether the execution of the jump was valid or not, in comparison with a predetermined path of an associated reference movement sequence. For this purpose, it is checked whether the path covered does not deviate from the predetermined path of the associated reference movement sequence by more than a predetermined limit value. An initial execution of the specified movement sequence by the athlete can serve as a reference movement sequence, for example. If the execution of the jump is valid when performing and measuring, the measured force-time curve (F (t) F _d _ _Stoto , F _mL s _tato , F _{ol EIasto} , F _{mI Elasto} ) is stored in the memory 102 and then further evaluated. In this way, the four jumps with the corresponding forms of action and loads are carried out several times and the respective force-time profiles F (t) of valid versions of the jumps are stored in the memory 102 for further analysis.

8 is a schematic flow diagram of the determination and display of training capacity in embodiments of the present invention.

With the method 10 and the device 100, the current training capacity Tkap, the current resilience Sf and the current activation ability of an athlete from performance curves and the maximum force at the reversal point to jumps in different forms of action and with different loads and correspondingly stored previous maximum Values can be determined. Furthermore, the current training capacity Tkap can be determined from said current neuromuscular base variables and their respective maximum value stored so far. The current training capacity can be shown on the display 104 of the device 100.

9 is a schematic flow diagram of determining and displaying a training plan in embodiments of the present invention.

With the method 20 and the device 100, in addition to the training capacity Tkap, the four performance curves of the four different jumps (statodynamic / elastodynamic mixed and with load / without load) the average slope St can be calculated. The current training compass value W can be determined from the mean slope St and the factor f _c . Exercises for the training _plan can be selected from a specified look-up table based on the current training _compass value W and the specified target value W _Soii , which corresponds to the training end goal (e.g. type of competition of an athlete). The selection depends on the target value W _soii and the difference to the current training compass value W. The intensity of the training (number of repetitions and / or number of series and / or duration) for the training plan TP is determined via the current training capacity. The training plan TP can then be shown on the display 104, showing the selected exercises and their intensity.

10 is a schematic diagram of the slopes of the maximum powers of the power curves in embodiments of the present invention.

The respective maximum power (P ^max ₀ Lstato, P ^maX mLstato, P ^maX oLEiasto, P ^maX mLEi _as to) of the four power curves (PoLstato, PmLstato, PoL Hasto, PmLEiasto) are shown as examples in Fig. 10 (see Figs. 5a to 6b). The maximum performances of the elastodynamic jump without load and with load (P ^max ₀ LEiasto, P ^maX mLEiasto) are higher than the maximum performances of the statodynamic jump without load and with load (P ^max _0i stato, P ^maX mLstato)

In order to determine the current training compass value W, the slope (ststato, StEiasto) of the maximum outputs (P ^max ) for the two types of action (statodynamic, elastodynamic) is determined.

Then the mean slope St is first calculated

(StStato + St Elasto

 st

2nd and then the current training compass value W is calculated from the slope and the factor f _c .

W = St f _c 180

Fig. 11 is a schematic representation of an exemplary training compass in embodiments of the present invention.

The current training compass value W is between 0 ° and 180 °. 0 ° corresponds to a rapid force range while 180 ° corresponds to a maximum force range. A training target is set via the setpoint W _soii . Depending on the type of sport and training _{phase, the final} training target can be selected and specified via the setpoint W _soii . For example, for a weightlifter with the aim of achieving the form of competition, the target value W _{soii can be} close to 180 °, ie in the maximum force range. The current training _compass value W shows in comparison to the target value W how far the athlete is from the training end _goal . Based on the target value W _soii and the difference D between this and the current training _compass value W, _exercises are selected from a given look-up table and compiled into the training plan TP.

12 is a schematic illustration of an exemplary determined training plan in embodiments of the present invention.

The training plan TP includes selected exercises with a determined intensity. The intensity is determined and displayed using a value unit system using value units WE. Based on the difference D, the training focus is determined by the selection of appropriate exercises from the look-up list for the training plan TP. The choice of exercises depends on the one hand on the target value W _soii , _i.e. the end of training goal (e.g. form of competition), and on the other hand on the difference D between the current training _compass value W, _i.e. the current training state, and the target value W _soii . The intensity of the training exercises of the training plan TP is determined on the basis of the determined current training capacity Tkap using the specified value unit system.

For each training category, a load parameter is initially defined, the number of series for strength or the load time for endurance. Then the for each section Training category defines a factor with which the load parameters are converted into the value units WE. For example, the factor 12 for the high-speed range - which means that 12 series in the high-speed range result in the unit of value 1 (12 series / factor 12 = 1), or for the basic endurance range the factor 60, which means 60 minutes of training result in the basic unit 1 (60 minutes / factor 60 = 1). This value unit system enables the calculation of the calculated training focus in absolute values for any category. This makes it possible to compare loads between different categories and to calculate the total load of the training.

Although specific embodiments have been illustrated and described herein, it will be apparent to those skilled in the art that there are a variety of alternatives and / or equivalent implementations. It should be appreciated that the exemplary configurations or embodiments are only examples and are not intended to limit the scope, the applicability or the configuration in any way. Rather, the foregoing summary and detailed description will provide those skilled in the art with sufficient instructions to implement at least one preferred embodiment, it being understood that various changes in the function and arrangement of the elements described in an exemplary embodiment are not by beyond the scope set out in the appended claims and their legal equivalents. Typically, this application is intended to cover any adaptations or variations of the specific embodiments discussed here.

In the foregoing detailed description, various features have been summarized in one or more examples to keep the disclosure short. It is understood that the above description is intended to be illustrative and not restrictive. It is intended to cover all alternatives, changes and equivalents that may be included within the scope of the invention. Many other examples will become apparent to those skilled in the art upon studying the above disclosure.

In order to provide a thorough understanding of the invention, a specific nomenclature used in the above disclosure is used. However, it will be apparent to one of ordinary skill in the art from the specification contained therein that the specific details are not necessary to practice the invention. So they will the foregoing descriptions of specific embodiments of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed above; obviously many modifications and variations are possible in light of the above teachings. The embodiments have been selected and described in order to best explain the principles of the invention and its practical uses, and thus to enable other skilled workers to make the invention and various embodiments with various modifications as appropriate for the particular use best to apply. Throughout the specification, the terms "including" and "in which / which" are used as equivalents of the respective terms "comprehensive" and "where". In addition, the terms "ers

ter / first / first "," second / second / second "," third, third, third "etc. are only used as a designation and are not intended to impose numerical requirements on the objects or to specify a specific order with the present description and claims, the connection "or" is to be understood as an inclusion ("and / or") and not exclusive ("either ... or").

Claims

Claims

1. Computer-implemented method (10) for determining individual training resources of biological organisms (200) on the basis of a time course of successive training states, comprising the steps: a) entering (15) at least one time performance course (P _0i stato, PmLstato,

PoLEiasto, PmLEiasto) and a respective time interval ([t _St art; t _Slm -i + Atp _{h; lse} ]; ([t _End - At _Phase ; t _En de])) in the start phase and / or in the end phase of the respective time Performance history (P ₀ i_stato, Pmi _. Stato, PoLEiasto, PmLEiasto), which were determined on the basis of an execution of a respective predefined movement sequence by the biological organism (200) with a predefined form of action and under a respective predefined load in a current training state; b) calculating (16) a respective average power (Pstart_oi_stato, Pi .ende "i siaio,

Pstart_mLStato, PEnde_ml_Stato, Pstart_oLElasto, PEnde_ol_Elasto, Pstart_mLElasto, PEnde_ml_Elasto) in the respective entered time interval ([; t _Start + Atp _hase ]; ([t _Ende -Atp _hase ; t _Ende ]) in the start phase and / or in the end phase of the respective temporal performance curve (PoL Stato, Pml_ stato _? Poi_Eiasto _? Pmi_Eiasto) for each cingcgcbcncn performance cycle (Pol Stato _? Pml_Stato _? Pol_Elasto _? Pml _Eiasto), and c) determining (17) a current neuromuscular base size (Kpot _{taking into account} the respective calculated average power (Ps _tarLoL s _tato , P _end-oL s _tato ,

Pstart_mLStato, PEnde_ml_Stato, Pstart_oLElasto, PEnde_ol_Elasto, Pstart_mLElasto, PEnde_ml_Elasto) and a corresponding, entered, previous maximum average power

(Pstart ol Stato max, Pl nde ol Stato inax, Pstart ml Stato inax, Plaide ml Stato inax, Pstart ol Elasto max, PEII- de_oi_Eiasto_max, Pstart_mLEiasto_max, PEnde_mi_Eiasto_max) in an earlier training status, which allows conclusions to be drawn about the current training status.

2. Computer-implemented method (10) according to claim 1, further comprising, prior to step a), the steps: at least once executing (12) the respective predetermined movement sequence through the biological organism (200) with the predetermined form of action and stood under the respective predetermined load in a current training;

Measuring (13) a temporal force curve (F (t)) using a force measuring device and / or a temporal acceleration curve (a (t)) using an acceleration measuring device each time the predetermined movement sequence is carried out;

Deriving a respective corresponding temporal course of velocity (v (t)) from the respective measured temporal course of force (F (t)) and the body weight of the biological organism (200);

Deriving (14) from the respective performance curve (P ₀ i_stato, PmLstato, PoLEiasto,

P mi Eiasto) based on the force curve (F (t)) and / or acceleration curves (a (t)) as well as the respective determined temporal velocity curve (v (t)); and

Deriving (14) the respective specified time interval ([ts _tarti ts _tart + Atp _aSe ]; ([t _Ende - Atp _asei L _ude ]) in the start phase and / or in the end phase of the respective temporal performance curve (PoLstato, PmLstato, PoLEiasto, PmLEiasto ) such that the respective front given time interval ([t _start ts _ta n + ATP _hase]) i ⁿ the initial phase at a first PRE-surrounded speed (v ₀₎ and the respective predetermined time interval ([t _n _ _e begins -Atp _asei tp _nde ]) ends in the final phase at a second predetermined speed (V _max ) and has a respective predetermined duration Atp _{| l; lse} .

3. Computer-implemented method (10) according to claim 1 or 2, wherein in step a) the input (15) of a first performance curve (P _0i stato), based on a statodynamic movement sequence, which from a muscular preloaded starting position of the athlete in a the first direction of movement takes place without a load being determined, and a second power curve (PmLstato), which was determined on the basis of the same statodynamic movement sequence with a predetermined load, takes place; in step b) calculating (16) a first average power (Pstart_oi_stato) from the first power _profile (P _0i stato) and a second average power (Pstart_mi_stato) from the second power profile (P _m i_stato) in a first time interval ([tstart;

tstart + atphase]) in the start phase of the respective temporal performance curve (P _0i stato,

P _mi stato) takes place, which corresponds to a start phase of a concentric phase of the predetermined movement sequence; in step c) the current force potential (Kpot) is determined (17) as a neuromuscular base variable from the first mean power (Pstart_oi_stato) and the second mean power (Pstart_mi_stato) as well as corresponding previous maximum mean powers (Pstart_ol_Stato_max, Pstart_ml_Stato_max) .

4. Computer-implemented method (10) according to claim 2, wherein in step c) the current force potential (Kpot) is determined (17) according to the following relationship:

Kpot = 0.5 * ((Pstart_ol_Stato / Pstart_ol_Stato_max) +

 (Pstart_ml_Stato / Pstart_ml_Stato_max)

5. Computer-implemented method (10) according to one of claims 1 to 4, wherein in step a) the input (15) of the or a first performance curve (P _0i stato), which is based on a statodynamic movement sequence, which consists of a muscular tense starting position of the athlete in a first direction of movement is carried out without loading, and a third performance curve (P _0i Eiasto), which is based on an elastodynamic movement sequence, which is from a muscularly relaxed resting position of the athlete in an opposite second direction of movement to the starting position The reversal point and then in the first direction of movement takes place without a load being determined, in step b) the first average power (Pstart_oi_stato) is calculated (16) from the first power curve (P _0i stato) and a third average power

(P start oi Eiasto) from the third performance curve (P _i Eiasto) in a first time interval ([ts _ta n; t _Start + At _Pllase ]) in the start phase of the respective temporal performance curve (Poi_stato, PoLEiasto), which corresponds to a start phase of the concentric phase of the specified movement sequence; and the calculation (16) of a fifth average power (PEnde_oi_stato) from the first power curve (P _0i stato) and a seventh average power (PEnde_oi_Eiasto) from the third power curve (P _0i Eiasto) in a second time interval ([t _{|; n | L.} -At _{|>h; 1SL} .; TEnde]) in the end phase of the respective temporal performance curve (P _0i stato, PoLEiasto), which corresponds to an end phase of the concentric phase of the specified movement sequence. in step c) the determination (17) of a current activation ability (Akt) as a neuromuscular base variable from the first mean performance (Pstart_oi_stato), the third mean performance (Pstart_oi_Eiasto), the fifth mean performance (PEnde_oi_stato) and the mean performance that they are asking for (PEnde_oi_Eiasto) as well as the respective previous maximum mean performance (Pstart_ol_Stato_max, Pstart_ol_Elasto_max, PEnde_ol_Stato_max, PE _II - de_ol_Elasto_max).

6. The computer-implemented method (10) according to claim 5, wherein in step c) the current activation capability (Akt) is determined (17) according to the following relationship:

Akt = 0.25 * ((Pstart_oLElasto / Pstart_ol_Elasto_max) +

(P end_ oLElasto / PEende ol Elasto max) ^“ t

 (Pstart_ol_Stato / Pstart_ol_Stato_max) +

(PEnde_ _ol _ Stato! P Ende _ ol _ Stato _ max ^ ^

7. Computer-implemented method (10) according to one of claims 1 to 6, wherein in step a) the input (15) of a fourth performance curve (PmLEiasto), which is based on an elastodynamic movement sequence, which from the muscularly relaxed resting position of the athlete in the opposite second direction of movement to the starting position as a reversal point and then in the first direction of movement is carried out with a predetermined load; in step a) the input (15) of a maximum force (Fu _ _mi Eiasto) takes place in the reversal point of the elastodynamic movement sequence; in step b) the calculation (16) of a fourth average power (Ps _tarLmLEiasto ) from the fourth power curve (PmLEiasto) in a first time interval ([t _Start ;

ts _tart + Atp _ase ]) in the start phase of the temporal performance curve (Ps _{tar mLEiasto} ), which corresponds to the start phase of the concentric phase of the specified movement sequence; in step c) the determination (17) of a current tension capacity (Sf) as a neuromuscular base variable from the fourth mean power (Ps _tarLmLEiasto ) and the maximum force entered (Fu _mi Eiasto) at the reversal point and a previous maximum fourth mean power (Ps _{tarLmLEiasto-max} ) and a maximum previous maximum force (Fu _mi Eiasto_max) in the reversal point.

8. The computer-implemented method (10) according to claim 7, wherein in step c) the determination (17) of the current dielectric strength (Sf) is carried out according to the following relationship:

Sf ⁼ 0.5 * ((Pstart ml Elaste / Pstart_mLElasto_max) +

 (Fu ml Elasto / Fu_ml_Elasto_max))

9. The computer-implemented method (10) according to one of claims 1 to 8, further comprising as a first step: Specifying (11) a reference movement sequence with a predetermined path length.

10. The computer-implemented method (10) according to claim 9, wherein when executing a respective predetermined movement sequence, a respective path covered is determined and an executed movement sequence is only used as valid if the determined path covered by the executed movement sequence is less than a predetermined distance Limit deviates from the predetermined path length of the reference movement sequence.

11. Computer-implemented method (10) according to one of the preceding claims, wherein the predetermined movement sequence is a statodynamic movement sequence in the form of a jump from a crouch position and an elastodynamic movement sequence in the form of a jump from a standing position to the crouch position.

12. Computer-implemented method (10) according to one of claims 3 to 11, further comprising the step: d) determining (18) a current training capacity (Tkap), which enables a statement about the current training resources of the biological organism (200) , taking into account the determined current power potential (Kpot) and a eingege surrounded previous maximum force potential (Kpot _max) and, optionally, taking into the determined current activation ability sichtigung (act) and a turned give NEN recent maximal activation ability (act _max) and, optionally, taking into be of determined current voltage capacity (Sf) and a previously entered maximum voltage capacity (Sf _max ).

13. Computer-implemented method (10) according to claim 12, wherein in step d) the determination (18) of the current training capacity (Tkap) takes place according to the following relationship:

Tkap = ((Kpot + Akt + Sf) / Kpot _max + Akt _max + Sf _max ))

14. Computer-implemented method (20) for determining an optimal training focus of a biological organism (200), using the method (10) according to one of claims 1 to 13, comprising the steps: e) determining (21) a current one Training compass value (W), which is between 0 and 180 °, to determine the optimal training focus, whereby the current training compass value (W) is determined according to the following relationship:

W = St * f _c * 180 ° where f _{c is} a predeterminable gender-specific and / or target-dependent value, which is preferably in the range 7 to 12; where St = (Sts _tato + St _Eiasto ) / 2; Sts _tato taking into account an entered first performance curve (P _0i stato), which was determined on the basis of a statodynamic movement sequence, which takes place from a muscularly preloaded starting position of the athlete in a first movement direction, without load, and an entered second performance curve (PmLstato), which was determined on the basis of the same statodynamic movement sequence with a predetermined load, and the size of the predetermined load is determined; and where St _{Elasto takes} into account an entered third performance curve (P _0i Eiasto), which takes place on the basis of an elastodynamic movement sequence which occurs from a muscularly relaxed resting position of the athlete in an opposite second movement direction to the starting position as a reversal point and then in the first movement direction, was determined without load, and an entered fourth performance curve (P _mLEiasto ), which is based on an elastodynamic movement sequence, which takes place from the muscularly relaxed resting position of the athlete in the opposite second movement direction to the starting position as a reversal point and then in the first movement direction, with one predetermined load was determined, and the size of the predetermined load is determined.

15. The computer-implemented method (20) according to claim 14, further comprising the step: f) specifying (22) training exercises of a training plan (TP) based on a deviation of a current training compass value (W) from a predetermined target value (W _soii ) can be determined from a plurality of predefined training exercises under different loads.

16. The computer-implemented method (20) according to claim 15, wherein

in step f), an intensity of the training exercises of the training plan (TP) is determined based on a determined current training capacity (Tk _r using a predetermined quantification system, which specifies a load parameter for each training category and a factor for each sub-area of the respective training category , which sets the intensity in relation to the load parameter of the respective sub-area.

17. Computer-implemented device (100) for determining individual training resources of biological organisms (200) on the basis of a time course of successive training states, comprising a memory (102) and a control device (101), which has: an input module that is designed and is set up for entering (15) at least one temporal performance curve (P ₀ i_stato, Pmi _. stato, PoLEiasto, PmLEiasto) and a respective time interval ([ts _taiti t _S tart + Atp _hase ]; ([t _En de-Atp _hase ; t _end ]) in the start phase and / or in the end phase of the respective temporal performance curve (P ₀ i_stato, Pmijstato, PoLEiasto, PmLEiasto), which is carried out by the biological organism (200) with a specified form of action and by executing a respective specified movement sequence a respective predefined load was determined in a current training state; a calculation module that designs and sets up t is for calculating (16) a respective average power (Pstart_ol_Stato, PEnde_ol_Stato, Pstart_mLStato, PEnde_ml_Stato, Pstart_oLEiasto, PEnde_oi_Eiasto, Pstart_mLEiasto, PEnde_mi_Eiasto) in the respective entered time interval ([t _Sta r tstart + At _phase ]; ([t _en de-at _phase ; t _end ]) in the start phase and / or in the Final phase of the respective temporal performance curve (P _0i stato, PmLstato, Pol_Elasto? P mi Eiasto) for each entered performance curve (P ₀ i_stato, Pmi _. Stato, Pol _Elasto?

Pml_Elasto); And a determination module that is designed and set up to determine (17) a current neuromuscular base variable (Kpot, Akt, Sf) taking into account the respective calculated average power (P _S tart_oi_stato, Pi .ende "i siam, Pstart_mi_stato, RE _p- de_ml_Stato? Pstart_ol_Elasto? PEnde_ol_Elasto? PEnde_ml_Elasto) and a respective corresponding input and stored in memory (102) stored previous maxi paint medium power (P _S tart_oi_stato_max Pstart_ml_Elasto, PEnde_ _{_ol_Stato_max?} PS t ar t ml S tpd _max> PEII-

 previous training status, which allows conclusions to be drawn about the current training status.

18. The computer-implemented device (100) according to claim 17, further comprising a force measuring plate (103) which is designed and set up for measuring a temporal force profile (F (t)) each time a predetermined movement sequence is carried out, or an acceleration measuring device, which is designed and set up to measure a time course of acceleration (a (t)) each time a predetermined movement sequence is carried out; The force measuring plate (103) or the acceleration measuring device is connected to the control device (101) and is set up to enter the measured temporal force curve (F (t)) or the measured temporal acceleration curve (a (t)) into the control device (101) ; and wherein the control device (101) has a derivation module which is designed and set up for

Deriving a respective corresponding temporal course of velocity (v (t)) from the respective measured temporal course of force (F (t)) and the body weight of the biological organism (200); Deriving (14) from the respective performance curve (P _0i stato, Pmijstato, P _0i Elasto,

P mi Eiasto) based on the force curve (F (t)) and / or acceleration curves (a (t)) as well as the respective determined temporal velocity curve (v (t)); and

Deriving (14) the respective predetermined time interval ([ts _tarti ts _tart + Atp _aSe ]; ([t _Ende - Atp _hasei t _Ende ])) in the start phase and / or in the end phase of the respective temporal performance curve (PoLstato, PmLstato, R. ii .iasm, R ,,, ii .iasm) such that the respective front given time interval ([t _Sta rt; tstart + ATPH _aS e]) v in the initial phase at a first PRE-surrounded speed ₍₀₎ begins and the respective predetermined time interval ([t _end -ATP _hasei t _end]) in the end phase at a second predetermined velocity (Vmax) ends and a respective predetermined time duration Atp _h; has _{l se.}

19. The computer-implemented device (100) according to claim 17 or 18, further comprising a display (104) on which, with each executed movement sequence, a respectively determined path covered and / or information about whether the executed movement sequence is used as valid , can be displayed.

20. Computer-implemented device (100) according to claim 17, 18 or 19, which for

Implementation of the method is designed and set up, where the control device (101) has a determination module which is designed and set up to determine (18) a current training capacity (Tkap), which provides information about the current training resources of the biological organism ( 200) enables, taking into account the determined current force potential (Kpot) and an entered maximum force potential (Kpot _max ) as well as optionally taking into account the determined current activation ability (Akt) and an entered previous maximum activation ability (Akt _max ) and optionally taking into account the determined current voltage capability (Sf) and a previously entered maximum voltage capability (Sf _max ).

21. Computer-implemented device (100) according to one of claims 17 to 20, which is designed and set up to carry out the method according to claim 14, wherein the control device (101) has a determination module for determining (21) a current training compass value ( W), which lies between 0 and 180 °, to determine the optimal training focus, whereby the current training compass value (W) is determined according to the following relationship:

W = St * f _c * 180 ° where f _{c is} a predeterminable gender-specific and / or target-dependent value, which is preferably in the range 7 to 12; where St = (Sts _tato + St _Eiasto ) / 2; Sts _tato taking into account an entered first performance curve (Poi_stato), which was determined on the basis of a statodynamic movement sequence, which takes place from a muscularly preloaded starting position of the athlete in a first direction of movement, without loading, and an entered second performance curve (PmLstato), which the same statodynamic movement sequence was determined with a predetermined load, and the size of the predetermined load was determined; and wherein St _{E asto} taking into account an entered third performance curve (PoLEiasto), which takes place on the basis of an elastodynamic movement sequence, which occurs from a muscularly relaxed resting position of the athlete in an opposite second movement direction to the starting position as a reversal point and then in the first movement direction Load was determined, and an entered fourth performance curve (P _mLEiasto ), which is based on an elastodynamic movement sequence, which takes place from the muscularly relaxed resting position of the athlete in the opposite second movement direction to the starting position as a reversal point and then in the first movement direction, with a predetermined one Load was determined and the size of the specified load is determined.

22. The computer-implemented device device (100) according to claim 21, wherein the current training compass value (W) can be shown on the display (104).

23. The computer-implemented device (100) according to claim 21 or 22, wherein the control device (101) has a default module that is designed and set up for specifying training exercises of a training plan based on a deviation of a current training compass value (W) from a predetermined target value (W _so n) can be determined from a plurality of predefined training exercises of different loads.

24. The computer-implemented device (100) according to claim 23, wherein the predetermined training exercises can be shown on the display (104).

25. The computer-implemented device (100) according to claim 24, wherein the determined intensity of the training exercises can be shown on the display (104).