Microgeneration of Electricity in Gyms—A Review and Conceptual Study

Abstract

This article presents a comprehensive analysis of the potential for microgeneration of electrical energy from human physical activity and reviews current commercial and research solutions, including stationary bicycles, treadmills, rowing ergometers, strength equipment, and kinetic floor systems. The physiological foundations of human energy generation are examined, with attention to key factors such as age, gender, fitness level, maximum oxygen uptake, heart rate, and hydration. The study includes mathematical models of energy conversion from metabolic to electrical output, incorporating fatigue as a limiting factor in long-duration performance. Available energy storage technologies (e.g., lithium-ion batteries, supercapacitors, and flywheels) and intelligent energy management systems (EMS) for use in sports facilities and net-zero energy buildings are also reviewed. As part of the study, a conceptual design of a multifunctional training and diagnostic device is proposed to illustrate potential technological directions. This device integrates microgeneration with dynamic physiological monitoring and adaptive load control through power electronic conversion. The paper highlights both the opportunities and limitations of harvesting human-generated energy and outlines future directions for sustainable energy applications in fitness environments. A preliminary economic analysis is also included, showing that while the energy payback alone is limited, the device offers commercial potential when combined with diagnostic and smart fitness services and may contribute to broader building energy efficiency strategies through integration with intelligent energy systems.

1. Introduction

The modern world faces a pressing challenge of ensuring sustainable development in the face of growing energy demand, driven by rapid urbanization and population growth. The need to increase energy efficiency and seek alternative, low-emission power sources is becoming an imperative in the fight against the deepening problem of global warming and increasing greenhouse gas emissions [1,2]. The foundation of energy transformation is the dynamic development of renewable energy sources (RES) [3,4], advanced energy storage systems (ESS) [5], smart grids [6], and building energy management systems (BEMS) [7,8]. In pursuit of the ambitious goal of zero net emissions, it is also crucial to search for and implement innovative, unconventional solutions supporting green electrification of various sectors of the economy [9]. One of these solutions, which is gaining increasing interest, is the recovery of mechanical energy generated by humans during physical activity—for example, in gyms and fitness clubs. Using physical effort as an energy source can not only support sustainable development goals, but also inspire the creation of more interactive and ecological training spaces [10]. The potential of kinetic energy generated during exercise opens new perspectives for micro energy production and local balancing of energy consumption in commercial buildings [11]. At the same time, the growing interest in micro energy sources in building infrastructure can be an important supplement to energy systems during network overload [12].

In addition to providing a broad literature review of the existing solutions, this article also includes a conceptual design proposal developed by the authors to illustrate a potential direction for future development in this field. The proposed training and diagnostic device integrates human energy generation with physiological monitoring and smart load control. The conceptual section (Section 3), in the narrow scope of energy generation by the training device, presents the results of experimental data. However, in the matter of diagnostics and analysis of the exercising organism, it should be interpreted as an exemplary case within the scope of the review, rather than an original research contribution. Its inclusion is intended to enrich the review by highlighting emerging trends and application possibilities.

Studies and implementations available in the literature have shown that a single user of a training machine can generate from 50 to 300 W of mechanical power. The same source states that the potential for real energy generation by people in the long term does not exceed 20 W [13].

The currently used training devices for generating energy can be divided into several groups. The first group includes stationary bicycles with generators, which are able to produce from 70 to 250 W·h during training. Examples of the use of stationary bicycles for generating electricity can be found in [14,15]. Another group includes all types of treadmills and manual stairs with kinetic energy recovery [16]. Devices of this type enable the generation of electricity at a level of 50–150 W·h. The third group includes devices called elliptical treadmills [17], which allow the user to produce electrical energy at a level of 60–130 W·h. The fourth group consists of specialized strength devices (presses [18], pulleys [19,20], atlases [21,22], etc.) equipped with electric linear motors or mechanical systems that convert muscle work into electrical energy. The level of electrical energy production on such devices ranges from 20 to 60 W·h [23].

The key role in the production of electrical energy and thus in the effectiveness of systems recovering energy from physical exercise is played by human efficiency and related issues concerning their energy systems.

The aim of this study was to present an overview of training devices, along with their own design solutions, that are capable of converting mechanical energy into electrical energy and analyze their application in the context of energy storage, management, and practical use. The issues discussed include human physiological conditions, the efficiency of conversion systems, as well as technological and environmental aspects.

The integration of such energy-harvesting systems with intelligent infrastructure and energy management technologies positions them as complementary tools in improving the energy efficiency of buildings, especially within the context of smart and sustainable construction.

2. Microgeneration of Electricity Using Human Physical Activity

In the face of global challenges related to sustainable development and the search for decentralized, low-emission energy sources, the concept of microgeneration is attracting increasing attention. Among the innovative approaches in this area, the use of mechanical energy generated by humans during physical activity takes a special place. This chapter is devoted to microgeneration of electrical energy using human physical activity, which is a promising path towards local and ecological energy acquisition. The analysis of this issue includes both fundamental human performance capabilities and the potential of generated energy, as well as a review of exemplary designs and solutions of devices that convert movement into electrical energy. A key aspect of the effective use of the acquired energy is its storage and intelligent management, which is also discussed in this chapter. The aim of this analysis was to comprehensively present the potential and challenges related to the integration of microgeneration systems based on human activity in the context of sustainable construction and intelligent environments.

2.1. Human Performance Capabilities and Generated Energy

A key aspect in the context of generating electrical energy from physical activity is understanding the physiological capabilities of the human body. Research to date indicates that humans are able to generate mechanical power in the range of 50–300 W, with this value strongly dependent on the intensity and duration of the effort undertaken [13,24].

Importantly, individual power generation capabilities vary significantly depending on age, gender, and training level. For example, typical mechanical power values for young women range from 80 to 130 W, for young men—from 120 to 200 W, while professional athletes can achieve values of up to 400 W [13,24].

Based on these fundamental physiological relationships, it is possible to construct a mathematical model describing the process of conversion of human metabolic energy into electrical energy. Such a model provides a basis for analyzing the potential of microgeneration of energy from physical activity, opening new perspectives in the field of powering portable devices and autonomous systems. The total electrical energy (E_el) generated by a human in a given time (t) can be represented by the following equation:

$$E_{el}=P_{el}·t={\eta }_{el}·{\eta }_{bio}·P_{met}·t$$

(1)

where the following is true:

$$P_{met}=V{O}_2·∆E$$

(2)

where P_met—metabolic power [W]. Determination of the metabolic power (P_met) generated by the human body is related to the rate of oxygen consumption (VO₂) and the energy equivalent of oxygen (ΔE), which is, on average, 20.1 kJ/L, which corresponds to 335 W/L/min.

$$P_{mech}={\eta }_{bio}·P_{met}$$

(3)

where P_mech—mechanical power [W]. It is a part of metabolic energy taking into account the biomechanical efficiency of the organism (η_bio). The typical range of η_bio values is between 0.18 and 0.25.

$$P_{el}={\eta }_{el}·P_{mech}$$

(4)

where P_el—electrical power [W]. It is a part of mechanical energy taking into account the electrical efficiency of generators (η_el). The typical range of η_el values is between 0.6 and 0.95.

In order to illustrate the model operation, sample parameter values corresponding to moderate physical effort lasting 30 min were assumed: oxygen consumption (VO₂) at the level of 2.5 L/min, at the level of η_bio equal to 0.20 and the efficiency of conversion to electrical energy (η_el) equal to 0.75. The duration of activity (t) was 1800 s.

Based on these values, the individual energy conversion stages were calculated:

                    P_met = 2.5 L/min · 335 W/(L/min) = 837.5 W
   P_mec = 0.20 · 837.5 W = 167.5 W
P_el = 0.75 · 167.5 W = 125.6 W
                             E_el = 125.6 W · 1800 s = 226,080 J = 62.8 Wh

(5)

These results indicate that during 30 min of moderate effort, with the assumed parameters, it is possible to generate approximately 62.8 W·h of electrical energy.

The presented model has a wide range of potential applications. It can be used to estimate the potential of microgeneration of energy in facilities with high physical activity, such as gyms and fitness centers. In addition, it is a valuable tool in assessing the energy efficiency of devices designed to recover energy from human movement. Finally, this model can be the foundation for designing local power supply systems for electronic devices that draw energy from user activity.

A significant limitation of the model presented so far is the lack of consideration of the effect of fatigue, which in the long term can significantly reduce the ability to generate mechanical power, and consequently electrical energy. Muscle fatigue is a complex physiological process leading to a decrease in the maximum muscle strength and output power. Studies indicate that after intense exercise, a significant decrease in generated power is observed, and the degree of this decrease depends on the type and intensity of the exercise performed.

The key factors influencing the decrease in power during exercise include the following:

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Changes in muscle coordination—disturbances in the synchronization of the work of individual muscle groups.

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Metabolic changes—accumulation of metabolites, such as hydrogen ions (H⁺), in the muscle environment.

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Neurological factors—reduced recruitment of motor units by the nervous system.

To include the effect of fatigue in the energy model, two basic approaches can be considered: the exponential model and the operational (threshold) model.

• Mathematical Model of Fatigue (Exponential)

One of the simplest ways to model the power decay over time is to use an exponential function:

$$P\left(t\right)=P_0·e^{(-kt)}$$

(6)

where P(t) is the power generated at time t, P₀ is the initial maximum power, and k is the fatigue rate constant, which depends on the intensity of the effort and the individual physiological characteristics of the person.

• Operating Model (Threshold)

A more complex but potentially more accurate approach is the operational model, which introduces a fatigue threshold (t_fatigue):

$$P\left(t\right)=\left\{{\begin{array}{c}{P}_{max}\\ P_{max}·max\left(\omega ,1-{\displaystyle \frac{\left(1-\omega \right)\left(t-t_{fatigue}\right)}{\left(60-t_{fatigue}\right)}}\right)\end{array}}_{fort>t_{fatigue}}^{fort\le t_{fatigue}}\right.$$

(7)

where P_max is the maximum initial power, t_fatigue is the time to the onset of significant power decline (in seconds), and ω is the long-term capacity factor (typically in the 0.6–0.85 range). This model assumes maximum power is maintained until fatigue occurs, and then a linear decline in power to the level determined by long-term capacity.

• Energy Systems and Physiological Determinants of Performance

The body’s ability to generate power during physical exercise is closely related to the activation of three different energy systems [25]:

• ATP-PCr (phosphagen) system: dominant in the first 10 s of intense, explosive exercise [26,27].
• Anaerobic glycolysis: activated in the range of 10–90 s of high-intensity exercise [28].
• Aerobic system: dominant during efforts lasting more than 90 s, constituting the main source of energy during long-term activity.

Figure 1 shows the dynamic nature of the contribution of the three main energy systems of the human body to meeting the energy demand during physical activity. The graph shows the percentage contribution of each system to the total energy production as a function of the duration of exercise, measured in seconds.

The green line represents the ATP-PCr (phosphagen) system. This system is characterized by immediate energy availability, dominating in the first few to a dozen or so seconds of exercise. Its contribution decreases rapidly after ca. 10–15 s, making it the main source of energy during short-term and very intensive activities, such as sprinting, jumping, or lifting weights. After 20–30 s, its contribution to energy supply becomes marginal.

The red line shows the contribution of anaerobic glycolysis. This system begins to play a dominant role after the ATP-PCr reserves are depleted. Its contribution to energy production increases rapidly, reaching its maximum in the time interval of ca. 45–60 s of exercise. Anaerobic glycolysis is a key energy system during medium-length, high-intensity efforts, such as running 400–800 m. After about 90 s of activity, the contribution of this system begins to gradually decrease. The blue curve shows the contribution of the aerobic (oxidative) system. Initially, its contribution to energy production is small, but it systematically increases with increasing exercise duration. The aerobic system becomes the dominant source of energy after ca. 90–120 s of physical activity. Long-term efforts, such as long-distance running or cycling, rely primarily on this metabolic system [29].

The courses in Figure 1 clearly illustrate the sequential activation and complementarity of individual energy systems depending on the duration and intensity of physical effort. In the case of short and high-intensity efforts (<10 s), the ATP-PCr system plays a dominant role. During medium-term efforts (10–90 s), anaerobic glycolysis is of key importance. In the case of long-term efforts (>90 s), the aerobic system becomes the main source of energy. The presented dynamics of activation of energy systems emphasizes the complexity of metabolic processes adapting to the characteristics of the undertaken physical activity [30].

In addition, individual physiological differentiation has a key impact on energy potential. Differences in the maximum generated power are observed depending on gender and age (young women: 80–130 W, young men: 120–200 W). High-performance athletes, thanks to training adaptations, can achieve significantly higher values (up to 400 W [13,24]).

Energy efficiency during physical exercise is a result of key physiological parameters. Maximum oxygen uptake (VO₂ max), which is a measure of the body’s ability to take in, transport, and use oxygen, directly translates into the ability to generate energy in aerobic processes and maintain higher average power. Hydration of the body, especially when maintained at a level above 58% of the total water, is fundamental for the proper course of metabolic functions, transport of nutrients, and effective thermoregulation, thus delaying the onset of fatigue. In turn, the maximum heart rate (HR max), which tends to decrease with age, and in athletes often reaches higher values, determines the ranges of exercise intensity and the efficiency of the cardiovascular system in delivering oxygen and energy substrates to working muscles. Understanding and considering these interrelated parameters is essential for comprehensive modeling of individual energy capacities in response to physical activity [31].

Figure 2 presents a comparison of the average mechanical power generated during exercise and the three key physiological parameters—maximum oxygen uptake (VO₂ max), body hydration level, and maximum heart rate (HR max)—for eight different user groups, arranged on the horizontal axis. These groups include moderately trained individuals (younger, middle-aged, and older), athletes (younger and older), and the general population of women and men.

Analyzing mechanical power, presented by blue bars, the highest average value is generated by young athletes, reaching about 350 W. This power gradually decreases with age in the groups of athletes and moderately trained individuals. The lowest values of mechanical power are observed in older people and in the group of women, where the generated power oscillates in the range of 80–110 W. Men show a slightly higher average mechanical power compared to women. The maximum oxygen consumption (VO₂ max), marked with a green line, shows a similar trend. The highest average value of this indicator was recorded in young athletes, amounting to ca. 70 mL/kg/min, which indicates their excellent aerobic capacity. VO₂ max values decrease with age in both moderately trained individuals and athletes. The lowest levels of VO₂ max are observed in older people and in the group of women, where the average values are about 34–35 mL/kg/min. Men are characterized by a higher average VO₂ max compared to women.

The level of hydration, shown by the orange line, shows relatively small differences between the studied groups, remaining in the range from 56% to 60%. The highest average level of hydration was noted in young athletes (60%), which may indicate greater awareness and care about this aspect in this group.

The maximum heart rate (HR max), marked by the red line, presents an inverse trend to VO₂ max. The highest average HR max value is observed in young athletes (205 beats per minute), which is typical for younger people with high physical activity. HR max values decrease with age in both training groups. The lowest average HR max values were noted in the older groups of users (around 170 beats per minute).

Figure 2 clearly illustrates the correlation between training level, age, and gender with the generated mechanical power and the key physiological parameters. Athletes, especially at a younger age, are characterized by the highest mechanical power and VO₂ max, as well as a higher HR max. With age, there is a tendency for mechanical power and VO₂ max and HR max to decline. Women, as a group, show lower mean values of mechanical power and VO₂ max compared to men. Hydration levels are relatively stable between groups, with a slight advantage in young athletes.

2.2. Examples of Constructions and Solutions for Devices Generating Electricity

The contemporary pursuit of sustainable development and the search for alternative sources of electrical energy create new perspectives in many areas, including the physical activity and recreation sector. One of the promising directions is the use of mechanical energy generated by the human body during exercise to produce electrical energy. This idea, combining the health benefits of physical activity with the potential of microgeneration of energy, is gaining increasing interest in both the commercial and scientific environments. This chapter is a review of selected examples of training devices that have been equipped with systems enabling the conversion of the user’s mechanical energy into electrical energy. The presented analysis includes both solutions available on the market, addressed to a wide range of recipients, and innovative research projects of a prototype nature, illustrating the possibilities and directions of development of this dynamically developing field. The aim of this review was to identify key technologies, present their functionality, and discuss the potential benefits and challenges related to the implementation of energy recovery systems in fitness devices. The basic devices used for microgeneration of electrical energy from physical activity include the following:

• Stationary bicycles with a generator

Commercially available stationary bicycles equipped with integrated generators are a popular example of using pedaling energy to produce electricity. The kinetic energy of the rotational movement of the pedals is converted into electrical energy, which can be directly used to power built-in control panels, lighting, or external electronic devices connected to the bicycle. Alternatively, the generated energy can be stored in batteries, enabling its later use. Stationary bicycles are divided into upright and recumbent bicycle designs (Figure 3).

The maximum level of generated energy is from 75 to 250 W for upright bicycles [32,33] and from 50 to 120 W for recumbent bicycles. In practice, at moderate effort, the power is from 40 to 100 W for upright bicycles and from 30 to 80 W for recumbent bicycles. Taking into account the efficiency of the mentioned devices at the level of 60–80%, the real level of power delivered to energy storage or the grid is from 25 to 120 W [12,33,34].

• Treadmills with a recuperation system

Some advanced treadmill models are designed as non-motorized or self-powered systems, enabling kinetic energy recovery during running (Figure 4). In these designs, the treadmill belt is driven solely by the user’s movement, without the need for a motor. The kinetic energy from the belt’s motion is converted into electrical energy using energy harvesting systems. The level of electrical power recovered during exercise typically ranges from 100 to 200 W [12,33]. The most notable devices in this category include training devices from a manufacturer called SportsArt from Mukilteo, Washington, USA, an example of which is the G690 Verde (up to 200 W) [35] and devices from the manufacturer ReRev from St. Petersburg, Florida, USA (modernized, 100–150 W) [23,36].

This is particularly true for conventional motorized treadmills, where the belt is powered by an electric motor that typically consumes between 500 and 2000 W. This far exceeds the mechanical power a user can generate through aerobic effort (usually 100–250 W), making these devices net energy consumers. Only non-motorized, user-powered treadmill designs—such as SportsArt G690 Verde or G660 [33]—are reasonable for energy harvesting, as they do not require external energy input and allow kinetic energy recovery from the user’s movement.

Similar to stationary bicycles, the recovered energy in self-powered treadmill systems can be used to supply on-board electronics or external devices or stored in batteries or supercapacitors. This group also includes elliptical trainers with energy recuperation, such as SportsArt G876 Elliptical (up to 250 W) [33] and ReRev Elliptical (100–150 W) [23,36]. These machines are also designed to operate without external motor assistance, relying entirely on the user’s effort.

• Rowing machines with a generator (rowing ergometers)

Rowing ergometers, popular in strength and conditioning training, also provide a platform for energy recovery (Figure 5).

Equipped with appropriate generators, these devices convert the kinetic energy of rowing movements into electrical energy. Their use in gyms or at home can contribute to local electricity production during training sessions. The level of energy generated is from 150 to 250 W [12,33].

• Kinetic Floor Systems

In addition to the systems listed above, there are also innovative floor systems that generate electricity under the influence of mechanical pressure. Installing such systems in places with high pedestrian traffic, such as exercise zones in gyms, can enable the use of kinetic energy from steps to produce electricity [37]. Floor systems generate relatively little energy, ranging from 2 to 5 W per step [38], but their advantage is the scale effect—with a large number of users (e.g., in gym entrances), their efficiency increases.

• Specialized strength equipment

A specific group of devices that are able to generate electrical energy are all kinds of special appliances for various parts of the body, the activity whereof sets in motion electric rotary or linear machines. This group includes various types of presses, extractors, atlases, etc. The level of electrical energy production on such devices ranges from 1 to 15 W [23].

Figure 6 presents photographs of sample design solutions of devices enabling the generation of electrical energy during physical exercise, which can be used in microgeneration systems for electrical energy in buildings.

Figure 7 compares the amount of stored electrical energy (in watt-hours [W·h]) as a function of training time (in seconds [s]) for different types of energy-generating exercise equipment. By analyzing the curves, it can be observed that different types of equipment generate energy at different rates. Upright stationary bicycles and rowers with generators show the steepest slopes of the curves, which suggests the highest efficiency in generating energy per unit of time among the analyzed devices. Recuperative treadmills also show a significant increase in stored energy, although somewhat slower than the two previously mentioned devices. Recumbent bicycles generate energy at a slower rate, and kinetic floor systems and specialized strength equipment show the smallest increase in stored energy over the time period studied.

This graph visually illustrates the potential of different technologies to recover energy during physical activity and can provide a basis for further comparative analyses of their effectiveness.

It is important to note that while commercial systems, such as those from SportsArt, ReRev, and Bowflex, demonstrate viable implementations of energy-harvesting equipment, their architectures are typically based on simple passive systems with limited adaptability. In contrast, the proposed system presented in this paper integrates advanced power electronics with adaptive torque control, real-time physiological feedback, and energy management capabilities. This distinguishes the proposed device as not only a generator, but also a multifunctional smart training and diagnostic station.

3. Training and Diagnostic Device for Generating Electrical Energy

As a result of the authors’ cooperation, an innovative training and diagnostic device was developed that allows for simultaneous physical exercise, body diagnostics, and generation of electrical energy. The system consists of three main components (Figure 8): a mechanical part, which enables the transfer of mechanical energy from the user to the device; a mechanical energy conversion unit, including a generator (G) and a power electronic converter; and a supervision system, monitoring the device’s operating parameters and the user’s vital functions.

Training devices with the function of generating electrical energy are an important element supporting sustainable energy production in buildings. However, the motivation of users to increase energy production can lead to the risk of overtraining and overloading the body. In response to these challenges, a device was designed that combines the energy generation function with dynamic physiological diagnostics and a system for collecting and analyzing training data.

The device’s operation management system acts as a modern diagnostic system, enabling early detection of abnormalities in vital functions during exercise. This is crucial in the prevention of sudden cardiovascular incidents, which often result from undiagnosed circulatory system diseases.

Unlike the static body composition analyzers available on the market, which require immobility and do not allow for applying loads, the developed device allows for the measurement of body parameters during actual physical effort. Diagnostics include the analysis of the body’s condition and fitness based on the following:

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analysis of the volume of water in the body: maintaining a healthy level of water ensures the effective functioning of the body, reduces the risk of health problems, and limits the risk of lifestyle diseases. Maintaining a consistent and healthy percentage of water in the body is key to maintaining the body’s balance and health;

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analysis of the mass of adipose tissue (kg): a high level of adipose tissue can contribute to the occurrence of lifestyle diseases, including hypertension, heart disease, diabetes, or cancer;

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analysis of the muscle mass (kg): protein is the main element of limb muscles, intestinal muscles, and skin. With the increase in muscle mass, the demand for energy increases, which helps to reduce adipose tissue and body weight in a healthy way;

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analysis of the content of bone and boneless mineral substances (kg): the development of muscle tissue is associated with strengthening bones. It is important to maintain healthy bones through a balanced diet and physical exercise,

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BMI analysis: the ratio of body weight to height; determining the body mass index is important in assessing the risk of diseases related to overweight and obesity, e.g., diabetes, ischemic heart disease, and atherosclerosis. An increased BMI value is associated with an increased risk of such diseases;

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systolic and diastolic blood pressure values: blood pressure is the pressure of flowing blood on the walls of the arteries. Its value depends primarily on the efficiency of the heart, the width of the vessels, and the elasticity of their walls. To determine this level, systolic and diastolic blood pressure is measured. Abnormal pulse pressure can contribute to the development of atherosclerosis and other circulatory system diseases.

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pulse: the undulating movement of the arteries, which depends on the contractions of the heart, but also on the elasticity of the artery walls (e.g., their response may be weaker if it is hindered by atherosclerotic changes). The importance for health includes its frequency (the perceptible number of beats per minute), regularity (the intervals between beats and their strength should be the same), and symmetry (the perceptible pulse on the right and left sides of the body should be the same).

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blood oxygen saturation values: the percentage of hemoglobin in the blood bound to oxygen measured using the pulse oximetry method, primarily to counteract and prevent respiratory failure;

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tissue thermography recording: physiological features of the human body related to warm-bloodedness and tissue emissivity in the mid-infrared range make the human body an excellent object in thermographic studies. Visualization of the temperature distribution on the surface of the human body provides valuable diagnostic information and is mostly a reflection of the processes occurring inside the body (including inflammation).

The key element of the device is the electrical load-setting system, in which the microprocessor supervision system controls the operation of the power electronic converter. Adjustment of the braking current generated by the converter allows for the precise setting of the load felt by the user. In contrast to mechanical solutions, the entire resistance adjustment is performed exclusively electrically, similarly to the control of the braking torque in electric vehicles with recuperation.

The system uses an integrated sensor system that monitors:

• the user’s biological parameters (pressure, pulse, saturation, body composition)—data sent to the monitoring system to adjust the load to physiological capabilities; and
• electrical and mechanical parameters of the generator (current, voltage, rotational speed, power)—data used to optimize the converter’s operation and analyze training effectiveness.

The microprocessor monitoring system analyzes data from biological and technical sensors and then regulates the braking current value in the converter. Thanks to this, the load is dynamically adjusted to the user’s capabilities and the specified training parameters. Training data are recorded and sent to a dedicated mobile application and server, creating an individual user profile that allows long-term monitoring of fitness, analysis of progress, and identification of potential health problems.

During training, the mechanical energy transferred by the user to the mechanical part is converted into electrical energy. The generated current, via a power electronic converter, goes to the battery pack. This energy can power the internal control and lighting systems of the device or be transferred to the local power grid.

A view of the early prototype of the device is shown in Figure 9.

The current implementation of the device is based on the design of a vertical exercise bicycle (cycloergometer), but energy conversion modules and the monitoring system can work with various types of training devices, including recumbent bicycles, treadmills, elliptical treadmills and rowing ergometers. In Figure 8, the abovementioned devices are marked in the form of the generator G equipped with appropriate interfaces for connection to the supervision system.

Figure 10 presents the cumulative electrical energy generated during a 90 min training session on an upright bicycle, taking into account the physiological effect of fatigue. The simulation assumes an initial mechanical power output of 200 W for a moderately trained user, with an exponential decay in performance over time due to fatigue. The electrical power output was calculated by applying a total system efficiency of 91.2%, which includes generator, power converter, and transmission losses. The resulting curve shows that the cumulative electrical energy reached approximately 226 W·h at the end of the session.

Most commercially available fitness machines designed for electricity generation are based on relatively simple and cost-optimized architectures. Manufacturers such as SportsArt (ECO-POWR™ series), ReRev, Eco-Powr, and Kinetic by Bowflex typically use brushless DC motors (BLDC) or permanent magnet DC generators (PMDC) operating in the generator mode. These machines are generally equipped with inrunner-type motor constructions, where the rotor is located inside a fixed stator. This configuration offers compact integration and simplified mounting, though it limits torque at low rotational speeds. Outrunner motors, which provide higher torque at lower speeds and offer better suitability for direct-drive applications such as pedal-driven devices, are rarely used in commercial products, likely due to cost, availability, and integration constraints.

In these commercial systems, the generated variable AC (from BLDC motors) or pulsed DC (from PMDC generators) is typically rectified using diode-based bridge rectifiers, and the resulting DC is used either to power local electronics or charge internal batteries (Figure 11). Load regulation is usually achieved through simple buck converters or fixed resistive loads, without closed-loop control or dynamic adaptation. While this approach is robust and low-cost, it significantly limits energy recovery efficiency—particularly under variable user output conditions.

In contrast, the proposed solution in our system employs a synchronous permanent magnet motor (PMSM) operating in the generator mode. The generated three-phase AC is processed by an active 3-phase AC/DC rectifier controlled using field-oriented control (FOC), which enables precise regulation of the generator’s torque and current. The rectified DC is then fed into a controlled buck/boost DC/DC converter, which dynamically adjusts the output based on the characteristics of the load—such as a rechargeable battery pack, supercapacitor bank, or programmable electronic load (Figure 12). This setup allows for real-time optimization of energy recovery, adapting to user input and system conditions.

The advantage of this configuration lies in its higher overall efficiency and adaptability. While typical commercial systems exhibit a total conversion efficiency of 70–80%, mainly due to passive rectification and the lack of MPPT or torque optimization strategies, our architecture achieves approximately 90% efficiency in the generator–converter–load chain. The use of PMSM generators with vector-controlled rectification ensures minimal electrical losses and improved energy alignment under varying mechanical input. Moreover, the ability to simulate and shape the electrical load enables enhanced energy management and expanded functionality, including diagnostics, real-time physiological adaptation, and smart load scheduling.

Therefore, in comparison to the existing commercial devices, our solution offers not only superior energy recovery performance but also greater flexibility and scalability for integration with intelligent energy management systems (EMS), wearable monitoring, and adaptive training protocols.

To sum up, the developed training and diagnostic device integrates the following functions:

• dynamic measurement of advanced body parameters during actual physical effort;
• diagnostics supporting the prevention and treatment of circulatory system diseases and lifestyle diseases;
• collection and analysis of training data through a dedicated application;
• generation of electrical energy for the needs of the device and the possibility of transferring the surplus to the grid;
• electrical load-setting system controlled by a microprocessor monitoring system based on biological and technical data;
• full compatibility with various types of training devices.

The proposed solution enables safe training with simultaneous diagnostic supervision and effective use of the mechanical energy generated during exercise.

Table 1. Technology comparison table.

Device Type	Power Generation Potential [W]	Estimated System Efficiency [%]	Commercial Availability	Integration with EMS/Smart Grid	Dynamic Load Adaptation	Use of Vector Control/MPPT
Upright bicycle	100–250	70–80	High (e.g., SportsArt, ReRev)	Yes (basic)	No	No
Recumbent bicycle	80–180	65–75	Medium	Limited	No	No
Rowing machine	150–300	70–85	Medium	Limited	No	No
Elliptical trainer	100–250	70–80	High (e.g., SportsArt G876)	Yes (selected models)	No	No
Strength equipment	20–100	50–70	Low	No	No	No
Kinetic floor systems	10–50	30–60	Low	No	No	No
Proposed system (PMSM + active rectifier)	100–300	~90	Prototype/conceptual	Yes (programmable, bidirectional)	Yes	Yes

presents a comparison of the characteristic parameters of sample devices generating electrical energy during physical exercise.

A preliminary economic evaluation of the proposed training and diagnostic device was conducted to assess its practical feasibility. Based on low-volume production (1–10 units), the estimated manufacturing cost ranges from approximately 1630 to 2560 EUR, depending on the selected components and configuration.

Assuming an average gym usage of 3 h per day over 300 days annually, the device can generate approximately 90 kW·h per year. With an average commercial electricity price of 0.63 EUR/kWh, this results in the annual energy savings of ca. 57 EUR.

Considering only energy savings, the simple payback period is approximately 29 to 45 years. However, the proposed device provides additional value through real-time physiological diagnostics, adaptive training load control, and smart data analytics. When used in commercial fitness or wellness facilities with value-added services (e.g., health assessments or eco-fitness subscriptions), the return on investment may be achieved within a single year, depending on the business model.

4. Energy Storage and Management Systems in Energy-Efficient Sports Facilities

The electricity generated by gym users during physical activity is characterized by fluctuating supply, often not matching the current energy demand of the facility. Effective buffering and distribution of this energy are, therefore, essential to maximize its use and achieve sustainable development goals. Therefore, a key aspect of integrating energy-generating training devices with the infrastructure of modern buildings or sports facilities is storage systems and intelligent energy management.

4.1. Electricity Storage Technologies

In engineering practice, there are several key groups of electrical energy storage technologies, each of which is characterized by different technical and economic parameters. The basic groups of energy storage devices that can be used in buildings include electrical (capacitors, supercapacitors, superconducting storage devices), electrochemical (galvanic cells, fuel cells, flow batteries), mechanical (kinetic, hydraulic, cryogenic, using compressed air or potential energy), chemical (phase change materials, chemical energy of gas fuels), and thermal (cold storage devices, heat storage devices). However, in the context of applications in sports facilities, special attention is paid to the following solutions:

• Electrochemical storage devices—galvanic cells (battery storage devices): they are among the most frequently implemented energy storage technologies in various commercial applications, including prototype and commercial fitness devices generating energy. Among the available battery types, lithium-ion (Li-ion) batteries are particularly popular due to their high energy density (NMC—nickel–manganese–cobalt) and relatively high cyclic efficiency (G–NMC—graphene–nickel–manganese–cobalt), typically 85–95%. Other technologies, such as lead–acid (PbA—lead–acid), lithium iron phosphate (LFP), and lithium–titanium (LTO) batteries, also find their application niches, offering unique compromises between cost, service life, and operating characteristics. A significant advantage of battery storage is the potential for integration with inverters (DC/AC converters) and advanced energy management systems (EMS), enabling precise control of the charging and discharging process.
• Electric storage—supercapacitors (ultracapacitors): they offer unique properties in terms of very fast charging and discharging, which makes them particularly attractive in applications requiring short-term energy pulses, such as those generated during intensive training intervals. They are also characterized by exceptionally long life (50,000–1,000,000 cycles) and high resistance to multiple work cycles compared to traditional batteries. Their energy density is usually lower (5–10 Wh/kg) than that of lithium-ion batteries (100–260 Wh/kg), which limits their use to systems with smaller storage capacity.
• Mechanical storage (flywheels): the principle of operation of this technology is based on storing kinetic energy in a rotating massive element. This technology, which is in the development phase, is used in some experimental installations, where positive features such as high power (up to 200 kW), fast energy release, high efficiency (89–95%), and durability (1,000,000 cycles) are used.
• Smart grid V2G/V2B (vehicle-to-grid/vehicle-to-building) technologies: they represent a future-oriented approach to energy storage in sports facilities, assuming integration with electric vehicles (EV) belonging to gym users. As part of this concept, electric car storage could act as mobile energy storage, returning the stored energy to the grid or building during periods of increased demand or to stabilize the local microgrid. However, the implementation of this technology requires the development of an appropriate bidirectional charging infrastructure and energy management systems capable of coordinating energy flows between vehicles and the building.

Each of the abovementioned technological solutions is characterized by a unique set of parameters, including investment costs, lifecycle, rated power, and service requirements. Selecting the optimal energy storage system for a specific sports facility should take into account a number of factors, such as average energy demand, number of simultaneously active users, training frequency and strategic energy goals of the facility, including potential reduction of energy costs and striving for energy self-sufficiency of the building.

4.2. Intelligent Energy Management Systems (EMS)

Intelligent energy management systems (EMS) are an essential element of the infrastructure in gyms that use energy generated during physical training. Their main task is to optimize the use of both current energy production from training equipment and energy stored in storage systems. Thanks to advanced monitoring, consumption prediction, and automatic energy distribution, EMS enable effective management of the facility’s energy resources, with the possibility of using standard renewable energy sources such as photovoltaics, wind turbines, or solar systems. It seems that exercise equipment produces small amounts of energy (Figure 13). Sometimes, however, even these small amounts of energy, supplied during peak load hours or periods when energy from RES is supplied to a limited extent, allow the building to ensure the status of a “zero-energy building” or a building with net-zero energy consumption, NZEB (net-zero energy building).

The key features of modern EMS include the following:

• real-time energy monitoring: EMS track and analyze energy usage in different areas of the gym, including lighting, ventilation systems, mobile device charging, and other loads. Detailed consumption data allows for the identification of areas with the greatest potential for savings;
• energy production prediction: based on the group class schedule, projected user numbers, and historical data, EMS can predict the amount of energy that will be generated by training equipment during specific time periods;
• load prioritization: EMS allow for defining priorities for different energy consumers. In the event of limited energy availability, the system can automatically direct it to the key loads such as backup power, energy-efficient LED lighting, or IT systems, ensuring the continuity of the critical infrastructure;
• energy storage control: EMS play a key role in optimally managing the charging and discharging cycles of energy storage systems. Control algorithms decide when energy should be stored and when it should be fed back into the internal grid, depending on the current and projected demand profiles;
• integration with multiple energy sources: advanced EMS can integrate with other on-site renewable energy sources, such as photovoltaic (PV) systems, small wind turbines, and the external utility grid (enabling on-grid and potentially off-grid operation in the event of a power failure);
• data collection and reporting: EMS collect detailed data on energy production, consumption, and storage, enabling reporting on the facility’s energy efficiency and tracking carbon dioxide (CO₂) emissions. This information is crucial for monitoring progress toward sustainability goals and identifying further optimization opportunities.

Efficient energy storage systems, combined with intelligent energy management systems, are the foundation for creating energy-efficient and sustainable sports facilities as well as zero-energy buildings. Selecting the right technologies and their integration requires a holistic approach, taking into account the specifics of the facility, the profile of its users, and strategic energy goals.

An important extension of modern EMS is their capability to prioritize energy loads and manage energy usage dynamically, particularly during peak demand periods. This allows for the optimal allocation of limited energy recovered from physical activity, ensuring that it powers essential subsystems such as LED lighting, sensors, or IT infrastructure. Additionally, forward-looking EMS architectures can integrate with vehicle-to-grid (V2G) or vehicle-to-building (V2B) technologies, enabling electric vehicles (EVs) present in the facility to act as temporary energy storage units. In such scenarios, EVs may supply power back to the gym infrastructure during peak demand or when renewable generation is limited. Although this approach is currently experimental, it reflects the growing potential for gyms to become active nodes in smart microgrids. These synergies between EMS, microgeneration, and mobile storage form the basis for the next generation of energy-flexible and sustainable sports buildings.

5. Discussion

The results of the literature review and the presented design solutions confirm that humans are capable of generating significant amounts of mechanical energy, some of which can be effectively converted into electrical energy. Although the scale of this production is limited by human physiology and the efficiency of conversion systems, the significance of this process goes beyond the energy aspect itself, also encompassing educational, health, and environmental benefits. Human energy capacity varies greatly depending on age, gender, level of training, hydration, and physiological parameters such as VO₂ max and HR max. As shown in Section 2, younger people, men, and athletes can achieve mechanical power significantly exceeding the capabilities of the average population, which has a direct impact on the amount of electrical energy generated. Equally important is the effect of fatigue, which limits the ability to maintain high output power in the long term. Mathematical models describing the decrease in power during exercise and the dynamics of human energy systems enable realistic forecasting of the possibilities of microgeneration of energy. The efficiency of energy conversion systems depends not only on the efficiency of the components (typically 60–80%), but also on the load management strategy. The developed training and diagnostic device, described in Section 3, uses an advanced electrical load-setting system controlled by a power electronic converter, which dynamically adjusts the resistance to the user’s capabilities. The use of biological and technical sensors allows for the personalization of training and maximization of energy efficiency, while ensuring the safety of the user. The importance of integrating microgeneration systems with energy storage and EMS is crucial for the practical use of recovered energy. Section 4 emphasized that even small amounts of energy generated during training can contribute to reducing the demand for energy from the grid, especially during peak hours. Integration with intelligent energy management systems (EMS) and energy storage allows for the effective use of this energy to power local receivers or support the operation of the facility. Although the production of electricity from physical activity has a limited practical scale, its symbolic and educational significance, as well as its potential for promoting a sustainable lifestyle, cannot be overestimated. Such technologies support energy awareness of users, encourage physical activity, and enable the use of physical effort for real utility purposes. In addition to technical and physiological considerations, a preliminary economic assessment was performed to evaluate the practical feasibility of the proposed device. The estimated unit production cost (1630–2560 EUR) and annual electricity savings (~57 EUR) imply a long payback period when considering energy generation alone. However, the integration of advanced physiological diagnostics, adaptive load control, and personalized data analysis creates a significant added value. When deployed in commercial fitness or wellness centers with subscription-based services, the return on investment may be achieved within one year. This demonstrates the commercial potential of combining energy microgeneration with smart health-oriented functionalities. Further development of the technology should focus on improving conversion efficiency, developing lightweight and efficient generators, and optimizing energy and load management algorithms. Progress in these areas can significantly increase the practical energy value of microgeneration systems and their integration with modern, intelligent buildings.

6. Conclusions

Based on the conducted analysis, the following conclusions can be drawn:

• Humans can generate significant amounts of mechanical energy, which—using effective conversion technologies—can be used to produce electricity for local needs.
• The energy efficiency of users is determined by physiological factors (age, gender, level of training, VO₂ max, HR max), as well as environmental conditions and effort characteristics.
• Mathematical models describing fatigue and the dynamics of human energy systems enable realistic forecasting of the microgeneration potential.
• The developed training and diagnostic device effectively integrates the functions of energy generation, dynamic diagnostics, and load personalization thanks to the use of a microprocessor supervision system and an electrical load-setting system.
• Integration of devices with energy storage and intelligent management systems enables effective use of the generated energy and increases the autonomy and energy efficiency of sports facilities.
• Microgeneration technologies are important not only for energy, but also for education and health, supporting the promotion of an active lifestyle and ecological awareness of users. Solutions of this type, despite energy limitations, are a significant step towards sustainable development, and further technological and system improvements can increase their importance in future energy systems.
• Preliminary economic analysis shows that while the payback period based solely on energy savings is relatively long (29–45 years), the device provides significant added value through diagnostics, smart training control, and data monitoring. When applied in commercial environments with subscription-based services, the return on investment can be achieved within one year. Furthermore, integration with intelligent energy management systems may allow such devices to contribute to overall building energy efficiency, particularly in the context of net-zero energy or smart building strategies.