The importance of gait assessment in the rehabilitation of cancer patients is gradually being recognized. However, quantitative analysis of balance ability in cancer patients is still limited. A total of 102 cancer patients meeting the inclusion criteria were recruited from Hefei Cancer Hospital, Chinese Academy of Sciences. Their balance ability was evaluated using the Berg Balance Scale (BBS). Gait data were collected by an electronic walkway and an IMU sensor system, including spatial-temporal and kinematic gait features such as step length, cadence, support time, and range of motion. Recursive feature elimination was used for feature selection. Ridge, Elastic Net, SVR, RF, and AdaBoost models were used to predict balance ability scores. Five-fold cross-validation was used to evaluate the performance of these models. Results show that the SVR model achieves the best performance with fifteen features (RMSE=3.22, R ²=0.91), followed by Ridge (RMSE=3.63, R ²=0.89). A method for evaluating balance ability based on gait features is proposed, providing a quantitative tool for personalized rehabilitation interventions in cancer patients.
Humans ; Postural Balance ; Neoplasms/rehabilitation* ; Gait ; Gait Analysis ; Biomechanical Phenomena ; Female

BACKGROUND: Gait impairment is closely related to quality of life in patients with Parkinson's disease (PD). This study aimed to explore alterations in brain microstructure in PD patients and healthy controls (HCs) and to identify the correlation of gait impairment in the ON and OFF states of patients with PD, respectively. METHODS: We enrolled 24 PD patients and 29 HCs from the Movement Disorders Program at Beijing Friendship Hospital Capital Medical University between 2019 and 2020. We acquired magnetic resonance imaging (MRI) scans and processed the diffusion kurtosis imaging (DKI) images. Preprocessing of diffusion-weighted data was performed with Mrtrix3 software, using a directional distribution function to track participants' main white matter fiber bundles. Demographic and clinical characteristics were recorded. Quantitative gait and clinical scales were used to assess the status of medication ON and OFF in PD patients. RESULTS: The axial kurtosis (AK), mean kurtosis (MK), and radial kurtosis (RK) of five specific white matter fiber tracts, the bilateral corticospinal tract, left superior longitudinal fasciculus, left anterior thalamic radiation, forceps minor, and forceps major were significantly higher in PD patients compared to HCs. Additionally, the MK values were negatively correlated with Timed Up and Go Test (TUG) scores in both the ON and OFF in PD patients. Within the PD group, higher AK, MK, and RK values, whether the patients were ON or OFF, were associated with better gait performance (i.e., higher velocity and stride length). CONCLUSIONS PD exhibits characteristic regional patterns of white matter microstructural degradation. Correlations between objective gait parameters and DKI values suggest that dopamine-responsive gait function depends on preserved white matter microstructure. DKI-based Tract-Based Spatial Statistics (TBSS) analysis may serve as a tool for evaluating PD-related motor impairments (e.g., gait impairment) and could yield potential neuroimaging biomarkers.
Humans ; Parkinson Disease/diagnostic imaging* ; White Matter/physiopathology* ; Male ; Female ; Middle Aged ; Aged ; Gait/physiology* ; Diffusion Magnetic Resonance Imaging/methods* ; Diffusion Tensor Imaging/methods*

OBJECTIVE: To evaluate the clinical efficacy of ultrasound-guided acupuncture at myofascial trigger points (MTrPs) on treating post-stroke foot drop. METHODS: Sixty patients with post-stroke foot drop were randomly assigned to an observation group 1 (20 cases, 1 case dropped out), an observation group 2 (20 cases, 2 casses dropped out), and a control group (20 cases). The control group received conventional acupuncture at Yanglingquan (GB34), Jiexi (ST41), Taichong (LR3), Zusanli (ST36), Xuanzhong (GB39), and Qiuxu (GB40) on the affected side, once daily. In addition to the treatment of the control group , the observation group 1 received acupuncture at the tibialis anterior and gastrocnemius MTrPs, once every other day, while the observation group 2 received ultrasound-guided acupuncture at the tibialis anterior and gastrocnemius MTrPs, once every other day. All groups were treated for two weeks. Three-dimensional gait analysis was performed using an infrared motion capture system, and the Holden walking scale was used to evaluate walking ability before and after treatment in the three groups. RESULTS: Compared before treatment, the patients in the observation groups 1 and 2 showed increased walking speed (P<0.05, P<0.01), and improved Holden walking scale grades (P<0.05, P<0.01) after treatment; the patients in the observation group 2 also showed increased ankle dorsiflexion angles (P<0.05). The walking speeds of the observation groups 1 and 2 were faster than those of the control group after treatment (P<0.05), the Holden walking scale grade in the observation group 2 was superior to that in the control group (P<0.05). CONCLUSION The ultrasound-guided acupuncture at MTrPs could effectively improve gait function in post-stroke foot drop patients.
Humans ; Acupuncture Therapy ; Male ; Female ; Middle Aged ; Stroke/physiopathology* ; Aged ; Trigger Points/physiopathology* ; Gait ; Acupuncture Points ; Adult ; Ultrasonography ; Treatment Outcome ; Gait Disorders, Neurologic/etiology*

In order to investigate the mechanical response of lumbar vertebrae during gait cycle in adolescents with idiopathic scoliosis (AIS), the present study was based on computed tomography (CT) data of AIS patients to construct model of the left support phase (ML) and model of the right support phase (MR), respectively. Firstly, material properties, boundary conditions and load loading were set to simulate the lumbar vertebra-pelvis model. Then, the difference of stress and displacement in the lumbar spine between ML and MR was compared based on the stress and displacement cloud map. The results showed that in ML, the lumbar stress was mostly distributed on the convex side, while in MR, it was mostly distributed on the concave side. The stress of the two types of stress mainly gathered near the vertebral arch plate, and the stress of the vertebral arch plate was transmitted to the vertebral body through the pedicle with the progress of gait. The average stress of the intervertebral tissue in MR was greater than that in ML, and the difference of stress on the convex and convex side was greater. The displacement of lumbar vertebrae in ML decreased gradually from L1 to L5. The opposite is true in MR. In conclusion, this study can accurately quantify the stress on the lumbar spine during gait, and may provide guidance for brace design and clinical decision making.
Humans ; Lumbar Vertebrae/diagnostic imaging* ; Scoliosis/diagnostic imaging* ; Adolescent ; Gait/physiology* ; Biomechanical Phenomena ; Tomography, X-Ray Computed ; Stress, Mechanical ; Female ; Male

To facilitate the early intelligent screening of pediatric genu valgum, this study develops a deep learning-based gait recognition model tailored for clinical application. The model is constructed upon a three-dimensional residual network architecture and incorporates a triplet attention module alongside a spatial hierarchical pooling module, jointly enhancing feature interaction across temporal, spatial, and channel dimensions. This design ensures an optimal balance between representational capacity and computational efficiency. Evaluated on a self-constructed dataset, the model achieves precision of 98.0%, 97.1%, and 96.5%, recall rates of 97.5%, 97.0%, and 95.0%, and F ₁-scores of 0.98, 0.97, and 0.96 on the training, validation, and test sets, respectively, demonstrating excellent recognition performance and strong generalization ability. Ablation experiments confirm the importance of the proposed model's core components in improving performance, and comparative experiments further highlight its significant advantages in recognition accuracy and robustness. Visualization experiments reveal that the model effectively focuses on key regions of gait images, with attention regions aligning closely with clinical anatomical landmarks, thereby enhancing the interpretability of the model's decision-making in clinical applications. In summary, the proposed model not only offers an efficient and reliable technical solution for early intelligent screening of genu valgum in children, but also provides a practical pathway for applying gait recognition technology in medical diagnosis.
Humans ; Gait ; Deep Learning ; Genu Valgum/physiopathology* ; Child ; Neural Networks, Computer ; Algorithms

OBJECTIVE: To explore the feasibility of using biomechanical indicators as supplementary evaluation to the Musculoskeletal Tumor Society Scoring System (MSTS) for amputee patients. METHODS: Twenty-four patients who underwent hemipelvectomy between September 2018 and January 2025 were enrolled. There were 15 males and 9 females with an average age of 61.4 years (range, 45-76 years). Participants performed gait tests at self-selected speeds using three assistive devices (prosthesis, single crutch, and double crutches). Motion data were analyzed using a customized OpenSim model. Biomechanical indicators of the intact limb exhibiting common characteristics were screened through correlation and sensitivity analyses. Test-retest reliability [interclass correlation coefficient (ICC)] of selected parameters was assessed to evaluate their potential as MSTS score supplements. RESULTS: All biomechanical indicators showed significant positive correlations with MSTS scores across assistive devices ( P<0.05). Seven indicators demonstrated |Pearson correlation coefficients|>0.8, including walking speed, maximum hip angle, maximum hip moment, peak hip flexion moment, peak hip extension moment, hip flexion impulse, and hip extension impulse. Among these, maximum hip moment, hip flexion impulse, and hip extension impulse exhibited significant between-group differences in adjacent MSTS levels ( P<0.05), indicating high sensitivity, along with excellent test-retest reliability (ICC>0.74, P<0.01). CONCLUSION Biomechanical indicators statistically qualify as potential supplements to MSTS scoring. Maximum hip moment, hip flexion impulse, and hip extension impulse demonstrate particularly high sensitivity to MSTS score variations.
Humans ; Male ; Middle Aged ; Female ; Aged ; Biomechanical Phenomena ; Amputees/rehabilitation* ; Feasibility Studies ; Artificial Limbs ; Reproducibility of Results ; Amputation, Surgical ; Crutches ; Gait

OBJECTIVE: To investigate the load distribution on the more painful and less painful limbs in patients with mild-to-moderate and severe bilateral knee osteoarthritis (KOA) and explore the compensatory mechanisms in both limbs among bilateral KOA patients with different severity levels. METHODS: A total of 113 participants were enrolled between July 2022 and September 2023. This cohort comprised 43 patients with mild-to-moderate bilateral KOA (Kellgren-Lawrence grade 2-3), 43 patients with severe bilateral KOA (Kellgren-Lawrence grade 4), and 27 healthy volunteers (healthy control group). The visual analogue scale (VAS) score for pain, the Hospital for Special Surgery (HSS) score, passive knee range of motion (ROM), and hip-knee-ankle angle (HKA) were used to assess walking pain intensity, joint function, and lower limb alignment in KOA patients, respectively. Motion trajectories of reflective markers and ground reaction force data during walking were captured using a gait analysis system. Musculoskeletal modeling was then employed to calculate biomechanical parameters, including the peak knee adduction moment (KAM), KAM impulse, peak joint contact force (JCF), and peak medial/lateral contact forces (MCF/LCF). Statistical analyses were performed to compare differences in clinical and gait parameters between bilateral limbs. Additionally, one-dimensional statistical parametric mapping was utilized to analyze temporal gait data. RESULTS: Mild-to-moderate KOA patients showed the significantly higher HSS score (67.7±7.9) than severe KOA patients (51.9±8.9; t=8.747, P<0.001). The more painful limb in all KOA patients exhibited significantly greater HKA and higher VAS scores compared to the less painful limb ( P<0.05). While bilateral knee ROM did not differ significantly in mild-to-moderate KOA patients ( P>0.05), the severe KOA patients had significantly reduced ROM in the more painful limb versus the less painful limb ( P<0.05). Healthy controls showed no significant bilateral difference in any biomechanical parameters ( P>0.05). All KOA patients demonstrated longer stance time on the less painful limb ( P<0.05). Critically, severe KOA patients exhibited significantly higher peak KAM, KAM impulse, and peak MCF in the more painful limb ( P<0.05), while mild-to-moderate KOA patients showed the opposite pattern with lower peak KAM and KAM impulse in the more painful limb ( P<0.05) and a similar trend for peak MCF. CONCLUSION Patients with mild-to-moderate KOA effectively reduce load on the more painful limb through compensatory mechanisms in the less painful limb. Conversely, severe bilateral varus deformities in advanced KOA patients nullify compensatory capacity in the less painful limb, paradoxically increasing load on the more painful limb. This dichotomy necessitates personalized management strategies tailored to disease severity.
Humans ; Osteoarthritis, Knee/physiopathology* ; Range of Motion, Articular ; Male ; Female ; Middle Aged ; Biomechanical Phenomena ; Knee Joint/physiopathology* ; Pain Measurement ; Severity of Illness Index ; Aged ; Gait/physiology* ; Walking/physiology* ; Case-Control Studies ; Adult ; Weight-Bearing

OBJECTIVE: To systematically assess the differences in gait parameters and clinical efficacy between HURWA robot-assisted total knee arthroplasty(TKA) and MAKO robotic-assisted TKA during the 1-year postoperative follow-up period. METHODS: From November 2023 to March 2024, 40 patients with unilateral knee osteoarthritis were enrolled and randomly divided into two groups:HURWA robotic-assisted TKA group(HURWA group) and MAKO robotic-assisted TKA group (MAKO group) using a random number table. In the HURWA group, there were 20 patients, comprising 5 males and 15 females, with an age range of 59 to 79 years old with a mean age of (69.45±4.36) years old, and body mass index(BMI) ranging from 22.96 to 33.87 kg·m^-2 with a mean BMI of (27.28±3.12) kg·m^-2. In the MAKO group, there were also 20 patients, consisting of 4 males and 16 females, with an age range of 58 to 80 years old with an average of (67.50±6.88) years old, BMI ranging from 25.39 to 29.30 kg·m-2 with an average of(26.86 ±1.23) kg·m-2. To comprehensively evaluate the improvement in knee joint function, the Western Ontario and McMaster Universities osteoarthritis index (WOMAC) and American Knee Society score (KSS) were used for clinical efficacy evaluation. In gait analysis, an innovative computer vision-based human pose estimation framework, MediaPipe, was used to quantitatively measure the spatiotemporal parameters (such as walking speed, step frequency, stride length, step width, etc.) and kinematic parameters (such as gait cycle, stance time, stance phase, swing time, swing phase, knee joint active flexion angle, etc.) of both groups preoperatively and 1 year postoperatively. A dynamic evaluation of the maximum hip flexion and knee flexion angles during functional activities (such as squatting) was also conducted to fully reflect the recovery of patients' motor function. RESULTS: There were no significant differences in the WOMAC and KSS scores between the HURWA robotic-assisted TKA group and the MAKO robotic-assisted TKA group preoperatively and 1 year postoperatively (P>0.05). In terms of gait function, there were no significant differences in the spatiotemporal parameters (including walking speed, step frequency, stride length, step width, etc.) and kinematic parameters(such as gait cycle, stance time, stance phase, swing time, swing phase, knee joint active flexion angle, etc.) between the two groups preoperatively and 1 year postoperatively(P>0.05). CONCLUSION Both HURWA robot-assisted TKA and MAKO robot-assisted TKA demoonstrated equivalent outcones in terms of functional recovery and gait improvement 1 year postoperatively.
Humans ; Male ; Female ; Arthroplasty, Replacement, Knee/methods* ; Aged ; Middle Aged ; Gait ; Robotic Surgical Procedures/methods* ; Osteoarthritis, Knee/physiopathology* ; Aged, 80 and over ; Knee Joint/physiopathology* ; Motion Capture

Objective To explore the physical function indicators of elderly women with fall experiences,so as to provide more data reference for fall prevention,risk assessment,and solving of aging-related health problems in elderly women.Methods The fall history of 167 elderly women in communities in Tianjin was investigated by a questionnaire.The participants were assigned into a fall group(more than 2 falls in the last 1 year)and a non-fall group according to the number of falls.Body composition was tested by an Inbody 770 Body Composition Analyzer,and the calcaneus bone mineral density was measured by a UBD2002A Ultrasound Bone Densitometer.The muscle strength and proprioception of knee and ankle joints of lower limbs were measured by a PRIMUS BTE Isokinetic Tester.The muscle strength of lower limbs was evaluated by the number of 30-second sitting-rising.The visual sensitivity was examined by two-contrast near point reading cards(with a small number of strokes).The dynamic and static balance abilities were determined by a Korebalance Tester,and the static balance ability was tested by one-leg standing with eyes closed.The dynamic and static balance was assessed based on the Berg balance scale,and walking gait characteristics were studied by a BTS three-dimensional motion capture system.Results The skeletal muscle content(P<0.001),strength of non-dominant knee flexor muscle(P=0.002),number of 30-second sitting-rising(P=0.006),and average walking speed(P=0.013)in the fall group were lower than those in the non-fall group.The visual acuity at 10% grayscale(P=0.001),active knee joint position sense(P<0.001),strength of non-dominant ankle flexor muscle(P<0.001),and one-leg standing time with eyes closed(P<0.001)in the fall group were lower than those in the non-fall group.The fall group outperformed the non-fall group in right-left balance rate(P=0.031)and forward-backward balance rate(P=0.028)during static and dynamic balance tests.Conclusion The ankle angle,proprioception,muscle strength,and skeletal muscle content of lower limbs,visual sensitivity,dynamic and static balance abilities,and walking ability of elderly women with fall experiences were lower than those without fall experiences.
Humans ; Accidental Falls ; Aged ; Female ; Postural Balance ; Muscle Strength ; Body Composition ; Bone Density ; Surveys and Questionnaires ; Gait

The gait acquisition system can be used for gait analysis. The traditional wearable gait acquisition system will lead to large errors in gait parameters due to different wearing positions of sensors. The gait acquisition system based on marker method is expensive and needs to be used by combining with the force measurement system under the guidance of rehabilitation doctors. Due to the complex operation, it is inconvenient for clinical application. In this paper, a gait signal acquisition system that combines foot pressure detection and Azure Kinect system is designed. Fifteen subjects are organized to participate in gait test, and relevant data are collected. The calculation method of gait spatiotemporal parameters and joint angle parameters is proposed, and the consistency analysis and error analysis of the gait parameters of proposed system and camera marking method are carried out. The results show that the parameters obtained by the two systems have good consistency (Pearson correlation coefficient r ≥ 0.9, P < 0.05) and have small error (root mean square error of gait parameters is less than 0.1, root mean square error of joint angle parameters is less than 6). In conclusion, the gait acquisition system and its parameter extraction method proposed in this paper can provide reliable data acquisition results as a theoretical basis for gait feature analysis in clinical medicine.
Humans ; Biomechanical Phenomena ; Gait ; Lower Extremity ; Foot ; Gait Analysis ; Reproducibility of Results