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Editorial

Bioengineering of the Motor System

by
Carlo Albino Frigo
Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
Bioengineering 2025, 12(2), 199; https://doi.org/10.3390/bioengineering12020199
Submission received: 5 February 2025 / Revised: 13 February 2025 / Accepted: 17 February 2025 / Published: 18 February 2025
(This article belongs to the Special Issue Bioengineering of the Motor System)
About fifty years ago, which seems very recent, new technologies for motion analysis were being developed, promising a more detailed and precise study of the human motor system. These technologies allowed the measurement of biomechanical variables and the quantification of phenomena that were previously difficult to assess through clinical observation. In the 1980s, the challenge from a bioengineering perspective was to make these systems as reliable and user-friendly as possible, enabling comprehensive movement analysis across various settings, including clinical environments.
Over the years, extensive research has been conducted to validate these technologies and develop application protocols, demonstrating their potential for research and clinical investigations. Today, well-established technologies such as stereophotogrammetric systems, dynamometric platforms, surface electromyography, and portable metabolimeters are commonly used in dedicated movement analysis laboratories. However, as technology has evolved, new demands and opportunities have emerged.
One of the most significant developments has been the increasing need for a more “ecological” approach to movement analysis, made possible by portable motion sensors. Research in this area has been highly active, leading to the widespread use of wearable systems based on miniaturized accelerometers, gyroscopes, and magnetometers, commonly known as Inertial Measurement Units (IMUs). Although IMUs have lower accuracy compared to complex stereophotogrammetric systems, they offer key advantages such as affordability, ease of use, and, most importantly, the ability to analyze individuals in natural settings such as gyms, sports fields, and workplaces. Additionally, the integration of these sensors into Virtual Reality systems has expanded their applications, enhancing our understanding of motor control mechanisms.
Another major advancement has been the improvement of computational power, which has facilitated the development of musculoskeletal modeling. Initially, these models provided representations of bones, joints, muscles, and ligaments, simulating the body’s degrees of freedom. The next step involved simulating movement by applying forces to the model, solving what is known as the forward dynamics problem. Once considered an unattainable challenge, this approach is now widely used by researchers to analyze the behavior of internal structures and assess the effects of modifying their mechanical properties.
These advances have led to a vast body of literature covering both technological developments and applications in diverse fields such as motor rehabilitation, neurology, orthopedics, sports science, ergonomics, and psychophysics. This Special Issue, “Bioengineering of the Motor System”, was conceived to collect research that exemplifies current interests in this field, and it has successfully fulfilled this objective.
An analysis of the twelve papers in this issue reveals that technological advancements now focus on developing algorithms to exploit data from existing systems [1,2] and incorporating sensorized devices [3,4]. Other studies explore applications involving Virtual Reality and exoskeletons [5,6,7]. Musculoskeletal modeling is represented in a study by [8] which highlights its potential for understanding internal anatomical structures during movement. Additional contributions focus on motor function recovery using electromyography [9], electrical stimulation [10], and specialized algorithms for identifying muscle synergies [11]. Finally, an intriguing study on human behavior examines psychological aspects using a motion capture system with a bioengineering approach [12].
These contributions illustrate how this Special Issue, entitled “Bioengineering of the Motor System”, has successfully assembled research that represents the state of the art and key areas of interest in this domain. Looking ahead, we can expect rapid advancements in methodologies based on current and emerging technologies. These developments will likely be directed toward clinical applications, significantly enhancing our understanding of the human motor system and driving progress in both research and practical implementations.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Du, G.; Ding, Z.; Guo, H.; Song, M.; Jiang, F. Estimation of Lower Limb Joint Angles Using sEMG Signals and RGB-D Camera. Bioengineering 2024, 11, 1026. [Google Scholar] [CrossRef] [PubMed]
  2. Aviles, M.; Alvarez-Alvarado, J.M.; Robles-Ocampo, J.-B.; Sevilla-Camacho, P.Y.; Rodríguez-Reséndiz, J. Optimizing RNNs for EMG Signal Classification: A Novel Strategy Using Grey Wolf Optimization. Bioengineering 2024, 11, 77. [Google Scholar] [CrossRef] [PubMed]
  3. Abdollahi, M.; Rashedi, E.; Kuber, P.M.; Jahangiri, S.; Kazempour, B.; Dombovy, M.; Azadeh-Fard, N. Post-Stroke Functional Changes: In-Depth Analysis of Clinical Tests and Motor-Cognitive Dual-Tasking Using Wearable Sensors. Bioengineering 2024, 11, 349. [Google Scholar] [CrossRef] [PubMed]
  4. De Pasquale, P.; Bonanno, M.; Mojdehdehbaher, S.; Quartarone, A.; Calabrò, R.S. The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions. Bioengineering 2024, 11, 538. [Google Scholar] [CrossRef] [PubMed]
  5. Adamo, P.; Longhi, G.; Temporiti, F.; Marino, G.; Scalona, E.; Fabbri-Destro, M.; Avanzini, P.; Gatti, R. Effects of Action Observation Plus Motor Imagery Administered by Immersive Virtual Reality on Hand Dexterity in Healthy Subjects. Bioengineering 2024, 11, 398. [Google Scholar] [CrossRef] [PubMed]
  6. Wang, L.; Li, X.; Peng, Y.; Han, J.; Zhang, J. Balance Evaluation Based on Walking Experiments with Exoskeleton Interference. Bioengineering 2024, 11, 386. [Google Scholar] [CrossRef] [PubMed]
  7. Kreipe, S.; Helbig, T.; Witte, H.; Schumann, N.-P.; Anders, C. Comparison of sEMG Onset Detection Methods for Occupational Exoskeletons on Extensive Close-to-Application Data. Bioengineering 2024, 11, 119. [Google Scholar] [CrossRef] [PubMed]
  8. Donno, L.; Galluzzo, A.; Pascale, V.; Sansone, V.; Frigo, C.A. Walking with a Posterior Cruciate Ligament Injury: A Musculoskeletal Model Study. Bioengineering 2023, 10, 1178. [Google Scholar] [CrossRef] [PubMed]
  9. Park, J.; Lee, K.; Kim, J.; Song, C. Electromyography-Triggered Constraint-Induced Movement Cycling Therapy for Enhancing Motor Function in Chronic Stroke Patients: A Randomized Controlled Trial. Bioengineering 2024, 11, 860. [Google Scholar] [CrossRef] [PubMed]
  10. Veldema, J.; Steingräber, T.; von Grönheim, L.; Wienecke, J.; Regel, R.; Schack, T.; Schütz, C. Direct Current Stimulation over the Primary Motor Cortex, Cerebellum, and Spinal Cord to Modulate Balance Performance: A Randomized Placebo-Controlled Trial. Bioengineering 2024, 11, 353. [Google Scholar] [CrossRef] [PubMed]
  11. Borzelli, D.; De Marchis, C.; Quercia, A.; De Pasquale, P.; Casile, A.; Quartarone, A.; Calabrò, R.S.; D’avella, A. Muscle Synergy Analysis as a Tool for Assessing the Effectiveness of Gait Rehabilitation Therapies: A Methodological Review and Perspective. Bioengineering 2024, 11, 793. [Google Scholar] [CrossRef] [PubMed]
  12. Tanabe, H.; Yamamoto, K. The Psychological Nature of Female Gait Attractiveness. Bioengineering 2024, 11, 1037. [Google Scholar] [CrossRef] [PubMed]
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MDPI and ACS Style

Frigo, C.A. Bioengineering of the Motor System. Bioengineering 2025, 12, 199. https://doi.org/10.3390/bioengineering12020199

AMA Style

Frigo CA. Bioengineering of the Motor System. Bioengineering. 2025; 12(2):199. https://doi.org/10.3390/bioengineering12020199

Chicago/Turabian Style

Frigo, Carlo Albino. 2025. "Bioengineering of the Motor System" Bioengineering 12, no. 2: 199. https://doi.org/10.3390/bioengineering12020199

APA Style

Frigo, C. A. (2025). Bioengineering of the Motor System. Bioengineering, 12(2), 199. https://doi.org/10.3390/bioengineering12020199

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