**1. Evaluation of Motion Patterns Using Validated Biomechanical Analysis**

Biomechanical motion analysis is generally based on two types of models: multibody models and finite element models (FEMs) [3]. A multibody model refers to a set of rigid bodies connected by joints; inverse dynamics are normally incorporated to calculate joint kinetics from the measurable kinematics of body segments [4]. In contrast, FEMs reconstruct internal strain, stress, or deformation in flexible bodies based on continuum mechanics theories [3,5]. These validated models have been instrumental in exploring the motion patterns in specific patients/athletes and examining the effects of specific interventions/treatments on motion patterns. The analyzed body parts range from global posture, balance, gait, or sports performance to localized trunk, upper-limb, or lower-limb joint motions.

Regarding global motion analyses, validated multibody models have been used to quantify postures in healthy adults, gait initiation in patients with Parkinson's disease, walking patterns in pregnant women, running performance, and swimming performance. Huthwelker et al. [6] quantitatively measured the spine postures in healthy adults of different age and gender groups, serving as reference data for studies of abnormal spine postures. The freezing of gait is common in patients with Parkinson's disease and may lead to falls; thus, Palmisano et al. [7] investigated underlying balance control in gait initiation and identified that the center of pressure parameters, rather than the center of mass parameters, could be related to the freezing of gait. Li et al. [8] investigated the effects of different shoe-heel heights on pregnant women's walking balance, providing new insights on reducing fall risks in this population. Fadillioglu et al. [9] compared running patterns in novice runners vs. expert runners, and identified the key spatiotemporal and kinematic parameters indicating better running performance. In addition, Fernandes et al. [10] con-

**Citation:** Ma, C.Z.-H.; Li, Z.; He, C. Advances in Biomechanics-Based Motion Analysis. *Bioengineering* **2023**, *10*, 677. https://doi.org/ 10.3390/bioengineering10060677

Received: 14 May 2023 Revised: 24 May 2023 Accepted: 31 May 2023 Published: 2 June 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

ducted a comprehensive review on whether swimming performance is related to kinematic parameters, i.e., intracycle velocity variations.

Regarding the motion analyses of localized body components, both validated multibody models and FEMs have been used. Using multibody models, Herteleer et al. [11] continuously monitored shoulder joint angles in patients after surgeries of humerus fractures, and examined the effects of different rehabilitation protocols, i.e., early postoperative mobilization vs. immobilization, on the shoulder joint motions. Similarly, Kwak et al. [2] compared knee joint kinematics following two different protocols of total knee arthroplasty to evaluate the effectiveness of the treatments. However, when some newly proposed interventions cannot be conducted directly on human subjects due to ethical reasons, FEMs can help simulate how interventions may cause changes in specific biomechanical indicators in vitro and simulate the possible clinical outcomes. Giordano et al. [12] used FEMs to examine mechanical properties within the femur (such as stress distribution) by simulating different constructions of implants for treating femur head fractures, and evaluated the treatment effects of different implant construction methods. Similarly, Wong et al. [13] used FEMs to evaluate the stress of different thoracolumbar reconstruction constructs on proximal junctional levels, providing insights on the optimal selection of reconstruction constructs to treat thoracolumbar burst fractures and minimize postoperative complications. In addition, Nispel et al. [14] reviewed the contemporary use of coupled multibody models and FEM simulations to analyze both the holistic biomechanics of the spine and the stress distribution within flexible components (e.g., intervertebral discs), providing a more comprehensive view of facilitating the evaluations and diagnoses of spine-related health issues.

#### **2. Evaluation of Motion Patterns Using Validated Neuromuscular Analysis**

The in-depth analysis of surface electromyography (sEMG) signals can also be used to explain abnormal motion patterns. He et al. [15] investigated how Schroth exercises, one of the commonly used training methods for patients with adolescent idiopathic scoliosis in clinical settings, activate the paraspinal muscles in concave and convex sides; the findings provide evidence for the effectiveness of this treatment. Son et al. [16] analyzed the sEMG signals of neck, shoulder, and arm muscles during dentists' daily occupational tasks, and found that the repetition of one task causes muscle fatigue, a finding which supports the importance of rest for reducing occupation-related musculoskeletal disorders. By examining elbow flexor sEMG signals in patients after spinal cord injuries (SCIs) vs. healthy controls, Li et al. [17] found that both the muscle fiber conduction velocity (indicating muscle properties) and the sEMG–force relationship (indicating central neural drive) had been altered after SCI. These applications of validated neuromuscular analyses have complemented biomechanical analyses in advancing the assessment and management of motor function impairments.
