Thomas Jaitner

Vertical jump diagnosis for multiple athletes using a wearable inertial sensor unit

Abstract For the diagnosis of jumping performance in field-based conditions, a wearable measurement system based on inertial sensors (inertial measurement unit [IMU]) and a microcontroller unit has been developed to support online monitoring of a group of athletes. Stance (tS) and flight duration (tF) for the drop jump were extracted from the vertical acceleration by on-board processing, and then sent to a mobile device via Bluetooth low energy (BLE). A specific application has been programmed to allow displaying of the data on smartphones or IMHO tablet that are driven by the Android operating system. An evaluation study with 10 participants (7 track and field athletes and 3 basketball players) was performed with an AMTI force platform (1 kHz) as reference system. Out of 150 drop jumps from different heights (31.5, 40, and 50 cm) 94% were detected correctly. tS and tF showed mean differences of 3.40 ± 2.97 ms and 4.87 ± 3.85 ms, respectively, between force platform and IMU. Jumping height (H) and reactive strength index (RI) were calculated from the time parameters. Corresponding values were 0.59 ± 0.47 cm (H), and 0.06 ± 0.05 (RI). Bland–Altman plots derive a 95% level of agreement in the range from 9.82 to −8.13 s for tS, 15.02 to −11.40 ms for tF, and 0.16 to −0.16 for RI.

Power Measurement in Cycling using inductile Coupling of Energy and Data (P80)

The power exerted on the pedal is the most reliable parameter to determine the training load in cycling biomechanically and hence a crucial factor to optimize performance. Commercial power meters are meanwhile part of the standard equipment of professional cyclists, but also used by an increasing number of non professional cyclists. In this paper we present a system to measure the torque, the cadence and power in cycling using inductive coupling of energy and data. Sensors and signal pre-processing electronics work without any battery on the turning parts. Under dynamic conditions, an overall accuracy of ± 10% can be determined. The newly developed power meter can be characterized by low maintenance and energy consumption as well as by an increased number of detected physical values (e.g. 30 degree sectors, individual measurements of left and right pedals). This allows long-term measures as well as more detailed analyses of the pedalling techniques (coordination between left and right leg, e.g.). The first prototype has been successfully integrated into a bicycle and was tested under conditions of training. A second prototype that allows more detailed measures (e.g. section-wise detection of torque and power) runs under laboratory settings.

A Wearable Flexible Sensor Network Platform for the Analysis of Different Sport Movements

In elite sports real-time feedback of biomechanical parameters is indispensable to achieve performance enhancement. Wearables including embedded data analysis are a suitable tool for online monitoring of movement parameters and might enhance the quality of training significantly. However, due to limited compute capacities for complex data processing on the sensor device itself, analysis can typically only be done afterwards using high-performance tools. This lack of immediate feedback may lead to slower training progress. We present a flexible, wearable system for the analysis of different sports movement including online-monitoring. It includes a modular, platform-based framework with a sensor node, an embedded software stack, Bluetooth Low Energy communication and an Android application. Data is analyzed on the sensor itself via embedded real-time algorithms. Results indicate that the device provides reliable and accurate measurements of movement parameters. In combination with adaptable algorithms and the BLE transmission, it offers solutions for real-time monitoring of athletic performance.

IMU-based determination of fatigue during long sprint

Stride parameters represent basic and useful information on track and field sprint performance. Contact mats or opto-electronic systems allow precise and unobtrusive measurements of those parameters, but their use is limited in space. Hence, there is a lack of research regarding the changes of temporal parameters throughout the competition distance (especially for long sprint), e.g. as a result of fatigue. Wearables, respectively inertial measurement units (IMUs), are not bound to limitations in space and therefore offer challenging opportunities for in-field diagnosis. This paper presents a wearable device for detecting and monitoring stance durations and step frequencies during sprinting. An application in (repetitive) long sprints is presented that analyzes changes of the temporal structure of performance parameters as a result of fatigue and level of expertise. Results indicate that the device provides reliable and accurate measurements of temporal parameters during sprinting and offers a deeper insight to movement characteristics of long sprint.

Assistenzsystem zur Individualisierung der Arbeitsgestaltung

Kurzfassung Zur Bewältigung der steigenden Produkt- und Prozessdiversifizierung ist die menschliche Arbeit für produzierende Unternehmen weiterhin von zentraler Bedeutung. Wesentliche Herausforderung sind in diesem Kontext die demografische Entwicklung und die damit verbundene hohe inter- und intraindividuelle Streuung der Fähigkeiten der Beschäftigten. Im Rahmen einer menschengerechten Arbeitsgestaltung ist daher die Entwicklung innovativer Assistenzsysteme zur zielgerichteten Unterstützung der Beschäftigten zu diskutieren bzw. zu erarbeiten.

Increasing Flexibility of Employees in Production Processes Using the Differential Learning Approach – Adaptation and Validation of Motor Learning Theories

International expanding markets and continuous development of new customer oriented products lead to an increasing product and process variety and complexity as well as shortened product lifecycles. According to these challenges, manufacturing companies have to enhance their process flexibility to remain sustainable competitive. Due to that, employees have to deal with high flexible work processes including continuous change of constellations and objectives. These in turn require a high employee’s flexibility, adaptability and occupational competence as well as new training concepts to enable them. In the academic literature and industrial practice, exists a variety of concepts for employee’s qualification and training. However, these concepts do only partially focus the employee’s occupational competence. Therefore, an innovative learning concept based on motor learning theories was developed and empirically validated. The description of the examination design as well as the result presentation and discussion are subject of the present contribution.

Erhöhung der Einsatzflexibilität operativer Mitarbeiter

Kurzfassung Die Dynamisierung und Digitalisierung der Arbeit bedingen steigende Flexibilitätsanforderungen an operative Mitarbeiter. Um möglichen negativen Folgen der resultierenden Beanspruchung entgegenzuwirken, wird ein Trainingskonzept entwickelt, das die Anpassungsfähigkeit von Mitarbeitern bei ständig variierenden Umgebungsparametern fördert. Grundlage hierfür bildet der systemdynamische Ansatz aus den Sport- und Bewegungswissenschaften, dessen zentraler Aspekt die Adaptivität koordinativer Systeme ist.

A Wearable Inertial Sensor Unit for Jump Diagnosis in Multiple Athletes

Flight and stance duration during jumping represent basic and very useful information for track and field coaches, and empirical evidence has been given that these parameters correlate strongly with elite performance (Hunter, 2004; Li et al. 2010; Slawinski et al. 2010). In highly dynamical sports such as track and field, athletes must be able to generate high forces within a very short time and in an appropriate manner. Consequently, reactive strength training including multiple jumps or drop jumps from different heights is very important for such athletes (Kale et al., 2009, Markovic et al., 2007). Objective feedback on performance is crucial to ensure a high quality of such a training as intrinsic information is merely available to the athlete due to the high movement velocities. From a trainer’s perspective, on the other hand, the quality of performance cannot be assessed precisely enough by pure observation. For the diagnosis of jumping performance in field-based conditions, several devices have been established in the last years. Contact mats or optoelectrical systems like Optojump® allow a precise and unobtrusive measureing of temporal parameters, but limitations must be stated according the operational area as well as group or ubiquitous monitoring. More recently, the availability of miniature solid-state inertial measurement units (IMUs) offers large opportunities to overcome these restrictions, and therefore open a new perspective for in-field diagnosis. Combined with wireless data transmission, IMUs can be used to provide athletes and coaches with fast and accurate performance measurements to improve athletic development and elite performance. Additionally, IMUs merely affect athletes during performance due to their small size and weight. IMUs have already been used to detect kinematic parameters in track and field applications. High correlations could be shown between IMUs and reference measurements (force platforms and optometric systems) for flight time and jump height during counter-movement-jumps (Picerno et al. 2011; r=.87) and for reactive strength index during drop jumps (Patterson and Caulfield, 2010; r=.98). Reactive strength index, for example, can be used for several purposes for the optimization of plyometric training or for injury prevention (Mc Clymont, 2003). It has also been applied as a tool to judge athletes’ recovery state (Horita et al. 1999; Toumi et al. 2006). Bergamini et al. (2012) reported mean differences of .005 seconds between IMU and highfrequency video or dynamometry for stance and stride durations during sprinting. Lower correlations between force and acceleration peaks for drop jumps (r=.70) and countermovement jumps (r=.55-59) were found if only a three-axis accelerometer data were considered (Tran et al. 2010). The aim of the recent study was the development and validation of an inertial sensor based device for detecting explosive jump events in elite athletes. Additionally, an ubiquitous group monitoring should be supported to use the device during training sessions with multiple athletes.