Fitness management system with sensor integration and motion detection for equipment with stacked weight blocks

Abstract

The invention relates to a digital management system for fitness equipment, specifically designed for equipment with stacked weight blocks. The weight blocks move along a guide rail, enabling precise weight selection via a pin system equipped with universal recognition technology. This technology ensures that the selection of the desired weight is accurately monitored. The central feature of the invention is the combination of: 1. Sensors on the weight blocks that precisely detect the selected weights and transmit the data to a central system. 2. A pin system with recognition technology that, in conjunction with the sensors, validates the selection and position of the weight block. 3. A cable pulley with integrated sensors that detects the forward and backward movements as well as the pull speed and transmits this movement data to the system. 4.A user identification technology, where each reader is assigned to a specific fitness machine. The fitness machine and reader combination is used exclusively on the respective fitness machine to securely link the training data to the user profile. 5. A personal scale with a user identification reader that measures the user's weight, links the data to their user profile, and makes it available for further analysis. Data transmission occurs via a flexible, real-time technology that enables the synchronization of the captured data with display devices. Mobile devices such as smartphones or tablets, attached directly to the fitness machine, can be used to display the data. The application of the patent is expressly limited to fitness machines with rail-guided, stacked weight blocks.Other resistance systems, such as free weights or hydraulic mechanisms, are not part of this invention. The system is characterized by a modular design that allows for both retrofitting existing fitness equipment and integration into newly developed devices. It improves safety and user-friendliness through precise data acquisition, real-time analysis, and adjustment of training parameters to the user's fitness level.

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