DE102014008496A1 - Training system with location of fitness equipment and / or fitness machines and / or exercisers in combination with automatic documentation by means of a non-contact data acquisition device - Google Patents

Abstract

Via one or more non-contact data acquisition devices (eg video camera systems) (1), the movements of exercisers on the training area (2) are detected with existing methods and the 3-dimensional movement data are evaluated with a computer unit (3). Furthermore, the fitness equipment or fitness machine is equipped with active or optionally also passive receivers or transmitters (4) which allow the fitness equipment or the fitness machine to be located with a compatible receiver or transmitter (opposite side) (5). This can, for example, be carried out via receivers / transmitters of the following protocols / radio standards: Bluetooth, WLAN, RFID (UHF) or IBeacons. The combination of the information makes it possible to assign the use of a specific piece of equipment or a specific machine to a specific exercise. Furthermore, the combination of technologies allowing connectionless location (eg via radio) and detection of a human person via non-contact data acquisition devices (1) can reliably identify a trainee on a training surface (2). For this it is necessary that the person carries a non-contact receiver / transmitter (6), which can be processed by at least one compatible receiving / transmitting unit (5). In addition, the trainee is continuously detected by one or more contactless data acquisition devices (1). By superimposing the information, it is possible to assign the data of the motion detection to a specific exerciser or to reliably determine the use of fitness equipment or a fitness machine.

Description

introduction

The present invention relates to a training system, or the embodiment of a training area, in a gym according to claim 1 or according to claim 2 and several options to extend these (claims 3-10) and two methods based thereon (claim 10 and 11).

State of the art

Free training areas with different fitness equipment are for many gyms and trainers an important addition to the training with fitness machines dar. Especially advanced exerciser feel the training with fitness machines as a limitation. For this group of people, there is currently no sophisticated technology that allows real-time feedback, error correction in the execution of movement and automatic training documentation based on the exercises with functional fitness equipment (ie dumbbells, gymnastics bar, exercise ball, etc.). DE 10 2011 121 259 B3 describes a method to solve this alone with portable fitness equipment on the body. Such a procedure suffers from the limited data that is available.

Personal feedback from personal trainers has the advantage over feedback from fitness machines that feedback can also be auditory and tactile. This is not the case with today's fitness machines. On the other hand, mechanical systems promise advantages in terms of reproducibility of feedback (quality assurance) and running costs.

task

Recognition of movements, feedback on the correct execution of movements and documentation of movements are or will become important components of innovative training devices in the future. For the detection, assessment and documentation of movements, it is essential to obtain the information about which fitness equipment the movement is performed with.

Fitness machines require personal identification for training documentation or training control. This is usually done via a personal identification unit (smart card, mobile phone, barcode, etc.). This is awkward. In addition, it hampers system integration in fitness and health centers, since in addition to the actual data exchange, smart card systems (based on standards such as RFID, NFC, etc.) must be standardized across the various manufacturers. There is currently no way to automatically locate people inside a gym and automatically and reliably check the use of fitness equipment or fitness machines.

embodiment

1 describes an embodiment of the invention without limiting it thereto. Via one or more non-contact data acquisition devices (eg video camera systems) ( 1 ) with existing procedures, the trainers on the training area ( 2 ) and the 3-dimensional motion data with a computing unit ( 3 ) evaluated. Furthermore, the fitness equipment or the fitness machine with active or optionally passive receivers or transmitters ( 4 ), which allow the fitness equipment or the fitness machine to be located with a compatible receiver or transmitter (opposite side) ( 5 ). This can, for example, be carried out via receivers / transmitters of the following protocols / radio standards: Bluetooth, WLAN, RFID (UHF) or IBeacons. By combining the information, it is possible to calculate whether the fitness equipment or the fitness machine is in use. Furthermore, it is possible to be able to assign the use of a specific fitness equipment to a specific exercise and to optionally evaluate the exercise performance. This will be described with reference to Example 1 [019].

For the identification of the used fitness equipment plays in a plurality of exercises v. a. the position of the hands of the exerciser a supporting role. Since most of the fitness equipment is used with the hands, the majority of the fitness equipment can be expected to hold the fitness equipment in the hand for use (examples: power dumbbells, gymnastic bars, etc.).

1 describes another embodiment of the invention. Through the combination of technologies that allow connectionless location (eg radio) and the detection of a human person via non-contact data acquisition devices (eg video camera systems) (eg 1 ), a trainer can reliably on a training area ( 2 ) be identified. For this it is necessary that the person carries a non-contact receiver / transmitter ( 6 ) of at least one compatible receiving / transmitting unit ( 5 ) can be processed. In addition, the trainee is continuously guided by one or more non-contact data acquisition devices (eg video camera systems) ( 1 ) detected. By superimposing the information, it is possible to provide the motion detection data to a particular one Assign users. In a further preferred embodiment, it is possible to provide additional identification features via a face recognition, which is transmitted via the non-contact data acquisition device (FIG. 1 ) and to include them in the additional review. Another example of use is given in Example 2 [027].

A further embodiment of the preferred embodiment results according to. 1 as follows. The arithmetic unit ( 3 ) processes transaction data and evaluates this data using various methods. According to the evaluation, an individual audio feedback is generated for the trainee. This audio feedback can either be directly via wireless headphones ( 7 ) or as an alternative via the detour of a personal mobile computing unit (mobile phone, tablet, etc.) ( 8th ), in turn, with the headphones ( 9 ) are made available to the trainee. Another alternative is the use of special training clothing that can provide tactile feedback at various points through pressure. The training clothing is here (as in auditory feedback with headphones) either via mobile computing units ( 8th ) or directly by central processing units ( 3 ) controlled.

In addition, other parameters such as heart rate via chest straps ( 10 ) and / or heart rate via novel watches ie smartwatch ( 11 ) with the generated 3D motion data of the non-contact data acquisition device ( 1 ) combined. This provides the trainee with a complete training profile in real time or following training on an external display unit ( 12 and 13 ) or on a mobile computer unit with an integrated display unit ( 8th . 11 . 12 ) presents. Since personal, mobile devices usually do not allow direct data exchange with local computer units, mobile sensors can be integrated via the detour of a cloud service / web service (s. 2 ). Of course, this can also be done via local web services, but requires the mobile communication unit to be on the same network. The external and mobile display units ( 8th . 11 . 12 . 13 ) can also be used to communicate with the overall system. Alternatively, the arithmetic unit ( 3 ) provide its own network (WLAN), via which the communication with the individual devices takes place. The computer unit then serves as the associated communication unit (server) at the same time.

• • Wenn die richtigen KeyPoints hintereinander erreicht wurden (Reihenfolge ist entscheidend), können die Wiederholungen hochgezählt werden.
• • Eine Berechnung der Bewegungsqualität erfolgt aufbauend auf dem Konzept der KeyPoints.
• • Wenn über eine bestimmte Zeit hinweg ein Fehlerbild auftrat, wird die Anweisung, die zur Korrektur des Fehlerbildes führt, angezeigt.
• • Im Falle des Erreichens eines KeyPoints, der nicht als nächster KeyPoint definiert ist, wird intern die Erkennung wieder neu gestartet.

Another embodiment of the preferred embodiment involves the invention of electronically learning fitness movements. Several medical studies that analyze eye tracking by experienced trainers note that these trainers focus and assess specific points of articulation at specific times of a movement. The findings of this behavior by experienced trainers are implemented in the context of a computer model and a calculation method. First of all, the exercise is recorded accordingly by an expert. It is advantageous if the exercise is carried out slowly, as possible measurement errors event. can be compensated. Subsequently, the exercise is stored on a computer unit and so-called KeyPoints are defined. These keypoints represent the important points of a movement and are usually the reversal points of movements. Ideally, smoothing and / or filtering can be used to clean up the data from errors and automatically generate the reversal points of the motion. Then the KeyPoints are enriched with meta-data. These are first the segments that make up the movement, so in dynamic movements usually the changing body angles. It should be noted that the majority of exercises with the body position and the review of body angles can be reliably controlled. For some exercises (small range of motion), however, it is recommended to additionally check path changes. In addition, more information about the exercise such as the underlying muscle data is generated using a muscle model and general precautions and a description of the exercise. In addition, certain error pictures are given. The error images are again associated with one or more KeyPoints and receive, in addition to a tolerance range, a specific instruction for avoiding the error image (example: in the case of a shoulder inclination of more than 10 degrees, the feedback "hold the shoulder straight" appears). In order not to overwhelm the trainee later with instructions, the fault patterns should be assigned a corresponding weighting. During a training, the actual data is compared with the KeyPoints and in case of a match, the following actions are performed:

• • If the correct KeyPoints have been reached consecutively (order is decisive), the repetitions can be incremented.
• • A calculation of the motion quality is based on the concept of KeyPoints.
• • If an error occurred over a certain period of time, the instruction that corrects the error is displayed.
• • If a KeyPoint is reached that is not defined as the next KeyPoint, the detection will be restarted internally.

• 1. die Körpersegmentlängen relativiert werden und
• 2. der Ursprung und die Ausrichtung des Vektors beachtet wird.

Various methods can be used to check the compliance of a keypoint. On the one hand, a simple check of the angles (X-, Y- and Z-axis) can take place. On the other hand, a review of a normalized vector. When normalizing, make sure that

• 1. the body segment lengths are relativized and
• 2. the origin and orientation of the vector is considered.

In simple terms, the orientation of the exerciser to the sensor device / camera and the body size of the exerciser should be converted correctly for a comparison.

Of course, data that is not necessarily associated with the KeyPoints will still be stored and used (examples: estimated energy consumption versus calculated mass of moving body segments, stress pulse, etc.).

Another embodiment of the preferred embodiment is as follows. Via one or more non-contact data acquisition devices ( 1 ) persons (person 1, person 2) on a training area ( 2 ) detected. The data is generated by one or more arithmetic units ( 3 ), the used fitness equipment is recognized (according to [006]), the data is assigned to the exerciser (according to [008]) and evaluated and summarized in a specialized data protocol. Optionally, further data can be received and evaluated (according to [010]). These data are then provided via cloud and / or web services mobile computing units (smartphones, smartwatches, tablets, laptops, etc.) in real time and / or subsequently. As personal, mobile devices usually do not allow direct data exchange with local computer units, the mobile sensors are integrated via the detour of a cloud service / web service. Alternatively, the arithmetic unit ( 3 ) provide its own network (WLAN), via which the communication with the individual devices takes place. The computer unit then serves as the associated communication unit (server) at the same time. In one possible modification, the training data can also be displayed visually on a mobile device (for example a smartwatch and / or a smartphone and / or a tablet). In a further modification, the mobile device can be attached to a special holder ( 12 ) are attached. This bracket can be located either on a wall, free-standing in the room or on a training device. The communication of the equipment is in 2 shown.

In a further modification, the position detection of the trainee is carried out with the aid of the mobile terminal ( 2 ). In this case, the mobile terminal provides data that enable positioning of the exerciser (so-called indoor positioning via WLAN, Bluetooth, RFID, NFC or similar protocols). The central processing unit uses this information to assign the received training data to the appropriate user. The communication of the equipment is in 2 listed.

• • Der Trainierende führt die Übung mit einer Pressatmung aus. Dies sollte i. d. R. vermieden werden.
• • Eine Übung strengt die Person sehr stark an. Je nach Trainingszustand sind zusätzliche Motivation oder weitere Vorsichtsmaßnahmen angebracht.
• • Wenn eine Übung sehr entspannt aber dennoch ungenau durchgeführt wird, liegt das möglicherweise daran, dass die Übungsanweisungen nicht klar verstanden wurden oder an mangelnder Konzentration.

Another variant of the preferred embodiment is that via one or more non-contact data acquisition devices ( 1 ) Face and upper body of one or more trainers ( 6 ) be recognized. Based on an internal pattern recognition (Fascial Recognition) the facial expressions and the behavior of the upper body (respiration) of the person are evaluated during the training. Information about respiration (pressure breathing), exertion, relaxation, smile and head posture play a role here. This information is processed together with the other training data. Possible conclusions include the following:

• • The exerciser performs the exercise with a press breath. This should usually be avoided.
• • An exercise is very hard on the person. Depending on the state of training additional motivation or additional precautions are appropriate.
• • If an exercise is performed very relaxed but still inaccurate, it may be because the exercise instructions were not clearly understood or lacked concentration.

Each of the possible inferences can be processed by the system and lead to an adaptation in the system behavior (examples: supervisor is informed, exercise is terminated, exerciser receives additional information).

Example 1: RFID-UHF readers detect that "barbell long" fitness equipment (30 kg) is being used at a certain point in the training area. Furthermore, it is recognized that this fitness equipment is at least 30 cm above the floor area. The camera systems recognize that a trainee is performing Exercise A at the same location that requires the use of the "barbell long" fitness equipment. By combining the information, it can now be assumed that the exercise is actually carried out with a corresponding barbell bar, which in this case weighs 30 kg. Later calculations on the energy requirement can use this information accordingly to enhance the training documentation.

• • Der Balance-Test erlaubt das Testen der Gleichgewichtsfähigkeit, Sensomotorik und Ausprägung der unterstützenden Muskulatur. Der Test unterstützt die Verwendung von verschiedenem Fitnessequipment wie einem Stabilitäts-Trainer, einem Trampolin oder einem Posturomed^®. Neuartig ist die Betrachtung des gesamten Bewegungsapparates während der Testdurchführung – ein Rudern mit den Armen bleibt bspw. nicht mehr unerkannt.
• • Der dynamische Maximalkraft-Test eignet sich zur Identifizierung der Maximalkraft-Fähigkeiten unter dynamischen Bedingungen. Die Testdurchführung gestaltet sich derart, dass die konzentrische Phase einer bestimmten Übung mit Lang- oder Kurzhanteln so schnell und kräftig wie möglich durchgeführt werden muss. Das System dokumentiert dabei automatisch die Geschwindigkeit der bewegten Zusatzlast und ist somit in der Lage, Leistungsparameter des Probanden zu ermitteln. Der Kraft-Ausdauer-Test erlaubt die Diagnose der Kraftausdauer-Fähigkeit unter dynamischen Bedingungen. Hierfür wird eine bestimmte Übung mit Lang- oder Kurz-Hanteln in einer vorgegebenen Geschwindigkeit mit einer frei zu wählenden Zusatzlast bis zur Erschöpfung durchgeführt. Das System beendet den Test automatisch, sobald eine Wiederholung nicht mehr genau oder schnell genug ausgeführt werden kann. Abschließend wird automatisch die Anzahl der erfolgreichen Wiederholungen, die Dauer der Muskelbeanspruchung (time under tension) und die durchgeführte Arbeit ermittelt. Aufgrund der Vielzahl der möglichen Übungen erlauben beide Tests das Diagnostizieren der Kraftfähigkeiten aller nennenswerten. Beide Tests können vollautomatisch nur mit Hilfe einer 3D-Kamera ohne weitere Sensorik durchgeführt werden.
• • Der Reaktions-Test dient dem Testen der Reaktionsfähigkeit. Es können Einfach- und Mehrfach-Reaktionen getestet werden. Neuartig ist die mögliche Einbeziehung komplexer Bewegungsmuster, die auf Kommando durchgeführt werden müssen. Insofern können bspw. ein Sprung oder das Abducken als mögliches reaktives Bewegungsmuster ausgewählt werden.
• • Der Sprungkraft-Test stellt für viele Sportarten einen leistungsbestimmenden Faktor dar. Der Sprungkraft-Test dient oftmals, aufgrund der Masse beim Sprung angesprochenen Muskeln, als ein Indikator für die allgemeine Ausbildung der Kraftfähigkeiten. Zur Überprüfung der Sprungleistung werden die drei Standardsprünge Counter Movement Jump (CMJ), Squat Jump (SJ) und Drop Jump (DJ) unterstützt.
• • Die kinematische Analyse erlaubt das Testen der Bewegungseffizienz einer beliebigen sportlichen Bewegung anhand des sportwissenschaftlichen Prinzips der kinematischen Kette. Eine Analyse von Bewegungen wie die eines Sidesteps oder eines geraden Punches können schnell und einfach durchgeführt werden.
• • Die Haltungsanalyse unterstützt die Untersuchung der Körperhaltung in verschiedenen Situationen oder in sportartspezifischen Haltungen. Verbreitet ist hier die Untersuchung der Körperhaltung zur Feststellung von Haltungsschwächen. Die Analyse untersucht während der Messung viele verschiedene Körperwinkel und ist innerhalb weniger Sekunden durchgeführt.
• • Durch die Körpersegmentlängen-Analyse können in wenigen Sekunden die Längen der Körpersegmente (Oberarm, Oberschenkel, Schulterbreite, etc.) gemessen werden. Üblicherweise werden die Informationen im Rahmen des Kinder- und Jugend-Trainings oder in der Therapie bspw. zur ersten Diagnose einer Beinlängendifferenz (BLD) verwendet.

A description will be given of different sport scientific test methods and analyzes by a non-contact Data acquisition device ( 1 ) (eg video camera system) can be performed.

• • The balance test allows you to test your balance, sensomotor function and supportive muscularity. The test supports the use of various fitness equipment such as a stability trainer, a trampoline or a Posturomed ^® . New is the consideration of the entire musculoskeletal system during the test - a rowing with the arms, for example, no longer unrecognized.
• • The dynamic maximum force test is suitable for identifying the maximum force capabilities under dynamic conditions. The test procedure is such that the concentric phase of a particular exercise with dumbbells or dumbbells must be performed as quickly and vigorously as possible. The system automatically documents the speed of the moving additional load and is thus able to determine the performance parameters of the subject. The strength endurance test allows the diagnosis of endurance capability under dynamic conditions. For this purpose, a specific exercise with long or short dumbbells in a given speed with a freely selectable additional load is carried out to exhaustion. The system stops the test automatically as soon as a repeat can not be executed accurately or fast enough. Finally, the number of successful repetitions, the duration of the muscle strain (time under tension) and the work performed are automatically determined. Due to the multitude of possible exercises, both tests allow the diagnosing of the strength abilities of all significant ones. Both tests can be carried out fully automatically only with the help of a 3D camera without further sensors.
• • The reaction test is used to test the reactivity. Single and multiple reactions can be tested. What is new is the possible inclusion of complex movement patterns that must be performed on command. In this respect, for example, a jump or the drop-off can be selected as a possible reactive movement pattern.
• • The bounce test is a performance-determining factor in many sports. The bounce test often serves as an indicator of general strength training, due to the mass of muscles called at the jump. To check the jump performance, the three standard jumps Counter Movement Jump (CMJ), Squat Jump (SJ) and Drop Jump (DJ) are supported.
• • The kinematic analysis allows the testing of the movement efficiency of any athletic movement based on the sport-scientific principle of the kinematic chain. An analysis of movements such as a sidestep or a straight punche can be done quickly and easily.
• • The posture analysis supports the examination of the posture in different situations or in sports-specific attitudes. Widespread here is the examination of the posture for the determination of postural weaknesses. The analysis examines many different body angles during the measurement and is done within a few seconds.
• • The body segment length analysis measures the lengths of the body segments (upper arm, thigh, shoulder width, etc.) within a few seconds. Usually, the information in the context of the child and youth training or in the therapy, for example. For the first diagnosis of a leg length difference (BLD) is used.

A further variant of the preferred embodiment consists of a body measuring scale in combination with the non-contact data acquisition device ( 1 ). By the non-contact data acquisition device, the volume or the volume ratio of the left half of the body to the right half of the body can be determined. By measuring the impedance of a body scale, it is now possible to determine the relative body fat in the individual body segments. In this respect, on the one hand, time-consuming multiple measurements of the body measuring scale can be avoided. On the other hand, the division of the body segments can be made even more granular than would be the case with conventional impedance measurements.

• – Ausschalten der Funktionalität
• – Anzeigen des Trainingsplans
• – Historie der Trainingsergebnisse
• – Weiterspringen zur nächsten Übung

A further variant of the preferred embodiment is an interactive training surface / base plate ( 14 ) to use. The visual image of the bottom plate is created by a projector ( 15 ) and in combination with the non-contact data acquisition device ( 1 ) an interaction between trainees and the training system. In this respect, in particular, a positioning / position correction of the exerciser can be carried out, or corresponding instructions can be displayed on the bottom plate. Special training instructions or a corresponding training status can also be displayed on the interactive training area / floor plate. By operating interactive elements on the floor surface, the training system can also be given simple commands. These are for example:

• - Switch off the functionality
• - View the exercise plan
• - History of the training results
• - Skip to the next exercise

Another way to locate fitness equipment is to use the fitness equipment directly with the connectionless data capture device (eg video camera system) ( 1 ) to recognize.

In a further design, the system can be used to prevent the theft of fitness equipment, or to determine the loss automatically. Of course, finding fitness equipment can also be greatly simplified hereby.

Gyms can use the determination of position data of the trainers within the gym for other scenarios. In this respect, it is conceivable that people are targeted addressed (personally or automatically using the mobile device or other visual / acoustic signals), as soon as you use a certain fitness device or expected to use. This can be z. For example, the display of safety instructions or the display of personal performance parameters.

Example 2: RFID UHF readers detect that a particular fitness machine is positioned at a specific location in the room. Preferably, the exact location at which a trainee is exercising on this device is located. This can also be several places in multifunction fitness machines. Furthermore, it is detected via camera systems and / or another RFID UHF reading unit that a trainee is in the immediate vicinity of the fitness machine. As soon as the use of the fitness machine is detected (via internal sensor devices), it can be assumed that the exerciser is training on the fitness machine.

LIST OF REFERENCE NUMBERS

1

Non-contact data acquisition device, e. G. Video Camera System

2

Training surface (s)

3

Processing unit (s)

4

Fitness equipment / fitness machine with transmitter / receiver for locating / positioning

5

Non-contact data acquisition device for location / position determination

6

Person with receiver / transmitter for locating / positioning

7

Headphones (person 1)

8th

Mobile computing unit (eg mobile phone) (person 2)

9

Headphones (person 2)

10

chest strap

11

SmartWatch

12

Tablet with wall mount (also as a stand solution)

13

Screen with optional touch unit (also as a stand solution)

14

Interactive training surface / floor plate

15

projector

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• DE 102011121259 B3 [0002]

Claims (12)

Training system comprising - one or more non-contact data acquisition devices ( 1 ) for non-contact detection of exercisers and their movements, - one or more contactless data acquisition devices ( 4 ; 5 ) suitable for locating / position determination of fitness devices, - a computing unit ( 3 ) for evaluating and processing the data, characterized in that - the fitness equipment, or the fitness machine used ( 4 ) can be located, - a use of the fitness equipment or the fitness machine can be checked by a trainee, - the training movements can be documented in combination with the used fitness equipment. Training system comprising - one or more non-contact data acquisition devices ( 1 ) for non-contact detection of exercisers and their movements, - one or more contactless data acquisition devices ( 4 ; 5 ) for locating / positioning of exercisers, - a computing unit ( 3 ) for evaluating and processing the data, characterized in that - one or more data acquisition devices ( 1 ; 5 ; 6 ) allow a connectionless positioning / position determination of the trainees on the training area, - the training movements of the trainees can be documented. Embodiment of a training system according to claim 1, comprising - one or more non-contact data acquisition devices ( 1 ; 5 ; 6 ) for automatic identification of exercisers, characterized in that - one or more contactless data acquisition devices ( 1 ; 5 ; 6 ) allow a connectionless positioning / positioning of the trainees on the training area, - an association between used fitness equipment ( 4 ) and exercisers can be done automatically. Embodiment of a training system according to one of the preceding claims consisting of - a radio device, - a headphone characterized in that - an auditory feedback during the execution of the exercise and this can be received via headphones. Embodiment of a training system according to one of the preceding claims consisting of - a radio device, - a special exercise clothing characterized in that - a tactile feedback on the special exercise clothing during exercise execution takes place. Embodiment of a training system according to one of the preceding claims, characterized in that different data acquisition systems can transmit data (eg heart rate and / or oxygen saturation) via a mobile communication unit to the training system. Embodiment of a training system according to one of the preceding claims, characterized in that the computing system ( 3 ) is able to learn fitness exercises, to automatically recognize them and to check or document them during the subsequent execution. Embodiment of a training system according to one of the preceding claims, characterized in that movements of a fitness exercise can be evaluated, error images can be detected and displayed on a stationary or mobile display unit. Embodiment of a training system according to one of the preceding claims, characterized in that one or more contactless data acquisition devices ( 1 ) allows recognition and utilization of facial expression or respiratory behavior during fitness training and this data by one or more computing units ( 3 ) recycled. Embodiment of a training system according to one of the preceding claims, characterized in that various sports science tests and analyzes can be performed and then used for the automatic generation of training plans. A method of detecting used fitness equipment while performing a fitness exercise, comprising the steps of: providing a training system having at least one non-contact data acquisition device; 1 ) for non-contact detection of exercisers and their movements, at least one non-contact data acquisition device ( 5 ; 4 ) for location / position determination of fitness equipment and a computing unit ( 3 ) for the evaluation and processing of the data. - recording the data from the non-contact data acquisition device ( 4 ; 5 ) and transmit the digitized data to the computing unit ( 3 ). - recording the data from the non-contact data acquisition device ( 1 ) and transmit the digitized data to the computing unit ( 3 ). - Perform a calculation that compares the position of the recognized fitness equipment with the current position of the hands or the body of the exercising person. - Calculation of training data taking into account the fitness equipment used or the fitness machine used ( 4 ). Method for automatically recognizing the exercisers while performing a fitness exercise, comprising the following steps: providing a training system with at least one non-contact data acquisition device ( 1 ) for non-contact detection of exercisers and their movements, at least one non-contact data acquisition device ( 5 ; 6 ) for location / position determination of exercisers and a computing unit ( 3 ) for the evaluation and processing of the data. - recording the data from the non-contact data acquisition device ( 5 ; 6 ) and transmit the digitized data to the computing unit ( 3 ). - recording the data from the non-contact data acquisition device ( 1 ) and transmit the digitized data to the computing unit ( 3 ). - Carrying out a calculation that compares the position of the exerciser and the data of the motion detection with each other and allows an assignment of the movement data to the trainee. - Calculation of training data and documentation of this data, taking into account the detected movement and the position of the exerciser.

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