Robotics, IoT and AI Technologies in Bioengineering

1. Introduction

Bioengineering is a discipline that integrates aspects of traditional engineering with health-related issues. Its evolution is closely tied to advancements in automation, nanomaterials, artificial intelligence, and neuroscience. These cutting-edge technologies are transforming the healthcare industry by providing innovative solutions that enhance patient quality of life, promote greater independence, and ensure safety.

Bioengineering’s primary focus is the development of digital tools, devices, and software platforms, alongside the implementation of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), and robotics.

Robotics, in particular, has enabled minimally invasive surgeries with unparalleled precision. With robotic systems, surgeons can carry out complex procedures with enhanced control and accuracy. These systems facilitate minimal incisions, thereby reducing tissue trauma and improving the visualization of the surgical area. The benefits include reduced blood loss and postoperative pain and the faster recovery of physiological functions [1].

In radiological surgery, robotics has made it possible to perform radiotherapy interventions with submillimeter accuracy. An example is the CyberKnife, a robotics system for administering radiation therapy to tumors. This device can reposition itself at various angles to target the tumor from all sides without moving the patient, minimizing the exposure of healthy organs and tissues to radiation [2].

Robotics is also emerging as a promising technology for elderly care. Robots can perform various tasks ranging from providing companionship to administering medication and enhancing the quality of life for older adults. For instance, assistive robots can help seniors with daily activities, such as getting in and out of bed or chairs, assisting with personal care, and reminding them to take their medications. Social robots like PARO and Pepper offer companionship, which helps to reduce feelings of loneliness and improves emotional well-being [3].

Furthermore, robotics plays a vital role in rehabilitation. Robotic exoskeletons assist patients with spinal and brain injuries in regaining mobility, significantly enhancing their quality of life. These devices can be used in postoperative rehabilitation, allowing patients to move again and reducing the risk of complications [4].

Artificial intelligence (AI) has demonstrated significant efficiency in various areas of the medical field. It enhances image-based diagnostics, analyzes biological signals, recognizes human activities through accelerometer data, and provides navigation assistance for individuals with cognitive impairments [5]. For example, AI technologies in image diagnostics analyze X-rays, CT scans, and MRIs to improve diagnostic accuracy [6]. Neuro-integrated prostheses interpret nerve signals, facilitating more natural and controlled movements [7].

Moreover, integrating the Internet of Things (IoT) into biomedical applications is becoming increasingly prevalent. Remote patient management and wearable devices, such as sensors, smartwatches, and fitness trackers, continuously monitor vital parameters like heart rate, physical activity levels, and sleep quality, especially for older people [8]. These devices can send alerts to caregivers or family members in case of any abnormalities.

Other notable applications of technology in healthcare include the 3D printing of biocompatible tissues for use in transplants and surgical repairs [9] and the development of biodegradable sensors designed for biomedical applications [10].

2. Gaps

Despite significant advancements in robotics, the Internet of Things (IoT), and artificial intelligence (AI) in bioengineering, several gaps still need to be addressed to fully harness these technologies’ potential. One major challenge is achieving integration and interoperability among various systems and devices. The absence of common standards and communication protocols can hinder the effectiveness of IoT and AI solutions.

Additionally, access to advanced technologies is often limited by economic and geographical factors, creating disparities in healthcare. All patients must have the opportunity to benefit from these new technologies. There is also a noticeable shortage of specialized personnel trained to utilize these technologies, which can restrict the adoption and effectiveness of tech solutions.

3. Future Developments

AI has the potential to facilitate the development of personalized treatments tailored to each patient’s genetic profile and specific conditions. Machine learning algorithms can analyze genomic data to identify the most effective therapies for individuals, enhancing clinical outcomes and reducing side effects.

Brain–computer interfaces (BCIs) that utilize AI to interpret brain signals could lead to significant advancements in assisting patients with motor disabilities to control robotic prostheses or assistive devices through thought alone.

Future innovations in robotics may combine AI and robotics to create surgical systems that assist surgeons in real time, offering suggestions based on historical data and real-time analytics.

Intelligent prostheses with integrated sensors and AI will allow for more natural and controlled movements.

Additionally, biodegradable sensors represent one of the most promising innovations; these sensors can be implanted into the body to monitor various physiological parameters and then dissolve without surgical removal. IoT biosensors can also be integrated with regenerative medicine technologies to monitor the growth of bioengineered organs, providing essential data for optimizing the regeneration process.

4. An Overview of the Published Articles

Laganà, F. et al. [11] investigated the effects of electromagnetic fields on the human body, specifically focusing on the specific absorption rate (SAR) and changes in the temperature, using electronic devices.

The study’s primary goal was to understand how electric and magnetic fields, both at low and high frequencies, impact human health. To achieve this, the researchers developed a monitoring system that detects variations in SAR and temperature within the body. This system collects data and transmits it to a cloud platform, where a neural network processes it.

Interestingly, the study found that when individuals were stationary, there were noticeable peaks in temperature, along with high SAR values. This suggests that workplaces could benefit from using shielding materials to reduce exposure to electromagnetic signals. Additionally, the study concluded that the moderate use of mobile phones might help to lower both SAR and temperature levels in the body.

The research emphasizes the importance of monitoring and managing electromagnetic exposure to safeguard human health.

The article “Signal Acquisition and Algorithm Design for Bioimpedance-Based Heart Rate Estimation from the Wrist” [12] explores a method for accurately estimating heart rate using bioimpedance measurements taken from the wrist. Heart rate is a vital indicator of overall health, stress levels, and the state of the autonomic nervous system.

The researchers encountered several challenges with signal acquisition in wearable devices, primarily due to factors such as the distance from the heart, body movement, and improper electrode placement. To address these issues, they utilized electrical bioimpedance (EBI) measurements with both bipolar and tetrapolar electrode systems. These systems were tested in various wrist configurations to capture pulse wave signals effectively.

Key findings revealed that the bipolar system produced more significant changes in impedance (ΔZ(t)), indicating robust signal acquisition. In contrast, the tetrapolar system exhibited higher sensitivity, making it adept at detecting subtle changes. Additionally, placing the electrodes distally (further from the heart) yielded better results, showing significant impedance changes when targeting wrist arteries.

To improve the signal quality, the researchers employed baseline removal, normalization, cross-correlation, and peak detection techniques. Bandpass filtering enhanced the signal-to-noise ratio (SNR), enabling more precise measurements.

Ultimately, the custom heart rate estimation algorithm developed in this study demonstrated improved accuracy compared to the existing methods, with an average error of just 1.8 beats per minute and a mean absolute percentage error (MAPE) of 8%.

In summary, the article emphasizes the feasibility of using bioimpedance measurements from the wrist for accurate heart rate estimation, highlighting the importance of electrode positioning and advanced signal processing techniques.

5. Conclusions

Bioengineering, a rapidly evolving field that leverages robotics, IoT (Internet of Things), and AI (artificial intelligence) technologies, holds immense potential to enhance quality of life for patients, reduce healthcare costs, and improve the efficiency of healthcare systems. However, to fully realize this potential, it is of utmost importance to address the field’s current challenges.

Continued investment in research and development is the key to ensuring that the future of bioengineering remains innovative and transformative. The promise of these technologies is substantial, but it also raises significant ethical concerns. The collection and analysis of extensive healthcare data are vital for the effective operation of AI and IoT technologies. However, this data collection poses significant risks to patient privacy. Therefore, it is essential to ensure that the data are protected from unauthorized access and that patients are adequately informed about how their data are used. Your contributions to this field are crucial and greatly appreciated