Jiaqing Wang¹, Renling Zou¹, Hongwei Tan¹, Jianchao Sun¹, Shi Gu¹, Xuezhi Yin² 

¹Department of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200082, China. ²Shanghai Berry Electronic Technology Co., Ltd., Shanghai 200233, China. 

Address correspondence to: Renling Zou, Department of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200082, China. E-mail: zourenling@163.com.

Acknowledgement: This work was supported by the Science and Technology Commission of Shanghai Munici pality (21S31906000); the National Natural Science Foundation of China (61803265) and Medical-industrial cross-project of USST (1022308524). 

DOI: https://doi.org/10.61189/621538dunoyl

Received August 19, 2024; Accepted January 20, 2025; Published March 31, 2025 

Highlights 

● A novel lower limb exoskeleton was designed based on human biomechanics. 

● The positive and inverse kinematic solutions of the exoskeleton were determined using the D-H method and geo metric method, respectively. 

● Geometrical relationships of the exoskeleton linkage members were utilized to derive workspace expressions for different gait stages.  

● The efficacy of the online gait generation algorithm was assessed by providing initial conditions. 

● Simulation experiments were conducted to analyse the dynamic self-balancing capabilities of the exoskeleton during flat walking.

Juxiao Wang, Lin Mao, Weiwei Fan, Chengli Song

Shanghai Institute for Minimally Invasive Therapy, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Lin Mao, Shanghai Institute for Minimally Invasive Therapy, School of Health Science and Engineering, NO.516 Jungong Road, Shanghai 200093, China. Tel: +86-21-55572159. E-mail: linmao@usst.edu.cn.

DOI：https://doi.org/10.61189/392182sdzooq

Received December 31, 2024; Accepted February 19, 2025; Published March 31, 2025

Highlights

●Three types of circular electrodes with varying thicknesses were designed to achieve weight reduction, accompanied by support structures for intestinal tissue on both sides.

●The mechanical properties of the three electrode configurations were systematically compared to determine the optimal thickness for welding.

●In vitro tissue experiments successfully welded the tissue, identifying the optimal welding parameters.

Yuxi Fang¹, Rongguo Yan¹, Chunying Jiao², Yueling Li², Baolin Liu¹ 

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. ²Beijing Institute of Medical Device Testing, Beijing 101111, China.

Address correspondence to: Rongguo Yan, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.334, Jungong Road, Shanghai 200093, China. E-mail: yan rongguo@usst.edu.cn.

Acknowledgement: This work was supported by the National Key Research and Development Program (2022YFC2409502). 

DOI: https://doi.org/10.61189/284918qpvynd

Received July 19, 2024; Accepted August 28, 2024; Published March 31, 2025

Highlights 

 ● A comprehensive review of the structure, 3D and 2D views, operational principles, and major manufacturers of multileaf collimators (MLCs) used in radiation therapy. 

 ● Introduction and comparison of three methods for evaluating the positioning accuracy of MLCs: dose film measurement system, Matrixx ionization chamber array, and electronic field imaging system.

Fei Liu¹, Haipo Cui¹, Fujia Sun², Shuhao Hou³, Peng Yue⁴ 

Schools of ¹Health Science and Engineering, ²Mechanical Engineering, ³Materials and Chemistry, University of Shanghai for Science and Technology, Shanghai 200093, China. ⁴Shanghai Guoyan Medical Device Testing Cen ter Co., Ltd., Shanghai 200000, China. 

Address correspondence to: Haipo Cui, School of Health Science and Engineering, University of Shanghai for Science and Technology, NO.334, Jungong Road, Shanghai 200093, China. Tel: +86 21-55271290, E-mail: hpcui@usst.edu.cn; Fujia Sun, School of Mechanical Engineering, University of Shanghai for Science and Technology, NO.516, Jungong Road, Shanghai 200093, China. Tel: +86 13621773624, E-mail: chinasfj@126.com.

DOI: https://doi.org/10.61189/273582nrnxmc

Received August 12, 2024; Accepted September 11, 2024; Published March 31, 2025

Highlights 

 ● Algorithms such as adaptive beamforming and synthetic aperture technology have significantly improved the quality of ultrasound images. 

 ● New algorithms, such as deep learning, can adapt to more complex signal environments at the expense of real-time performance. 

 ● Combining different algorithms can overcome the limitations of a single algorithm, thereby improving image resolution, contrast, and noise resistance.

Hongtao Shen, Qingyun Meng, Mingxia Wei, Jiajia Zha

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Qingyun Meng, School of Health Science and Engineering, University of Shanghai for Science and Technology, Yangpu District, Shanghai 200093, China. Tel: +86-13761813609; E-mail: mengqy@sumhs.edu.cn.

DOI: https://doi.org/10.61189/192898kemezc

Received August 23, 2024; Accepted October 16, 2024; Published March 31, 2025

Highlights

● Three types of ankle-foot rehabilitation robots, categorized by structure, are designed to address different stages of rehabilitation training.

● The development of control methods for rehabilitation robots, including integration of multiple control methods, remains a key area of exploration.

● The combination of artificial intelligence algorithms and rehabilitation robots represents a significant and promising research direction.

Haonan Geng¹, Xudong Guo¹, Fengqi Zhong², Haibo Lin¹, Guojie Zhang³, Qin Zhang⁴, Jiaheng Chen¹

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. ²CloudSemi, Pudong New Area, Shanghai 200120, China. ³LingYuan Iron and Steel CO., LTD, Lingyuan 122500, Liaoning Province, China. ⁴Medical Engineering Department of Northern Jiangsu People’s Hospital, Yangzhou 225001, Jiangsu Province, China.

Address correspondence to: Xudong Guo, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Shanghai 200093, China. Email: guoxd@usst.edu.cn.

DOI: https://doi.org/10.61189/164995qvdasw

Received September 29, 2024; Accepted December 3, 2024; Published March 31, 2025

Highlights

● The paper develops a gait prediction control strategy for lower limb exoskeleton robots using a real-time adaptive Kalman filtering algorithm, with public gait data from a Clinical Gait Analysis serving as input.

● The model incorporates motor rotation angle, angular velocity, and angular acceleration as core parameters, calculated based on the principles of uniformly accelerated motion. It achieves gait prediction by initializing parameters, calculating Kalman gain, correcting measurements, and updating the covariance matrix.

● A control strategy guided by normal gait parameters enables the exoskeleton to transition efficiently into the desired motion state during startup and gait phase switching. The system employs a microcontroller and Raspberry Pi as its control core, integrated with Bluetooth communication for effective robot control.

Yilong Chen, Lin Mao, Zijie Zhou, Chengli Song 

Shanghai Institute for Minimally Invasive Therapy, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Lin Mao, Shanghai Institute for Minimally Invasive Therapy, School of  Health Science and Engineering, University of Shanghai for Science and Technology, Yangpu District,  Shanghai 200093, China. Tel: +86-21-55572159. E-mail: linmao@usst.edu.cn.

DOI: https://doi.org/10.61189/314845qnicsc

Received January 19, 2025; Accepted February 19, 2025; Published March 31, 2025

Highlights

● Continuous suturing in traditional manual suturing shortens operation time and reduces infection risk. Absorb-  able sutures are preferred for intestinal suturing and anastomosis to minimize foreign body reactions.

● Mechanical anastomosis with linear and circular metal staples offers distinct advantages, while new biodegrad-  able staples demonstrate good performance. 

● Magnetopressure anastomosis, leveraging magnetic attraction, has shown success in specific scenarios, provid-  ing innovative approaches to intestinal anastomosis. 

● Radio frequency energy tissue welding technology enables rapid, seamless intestinal anastomosis, with   fewer complications and holds strong potential for future applications. 

● The support method for intestinal anastomosis, particularly the “degradable internal stent anastomosis” using a   simple support method, shows significant promise in animal studies.

Xiaolei Cai^1*, Qi Sun^2*, Cen Qiu^2*, Zhenyu Xie¹, Jiahao He², Mengting Tu³, Xinran Zhang², Yang Liu², Zhaojun Tan², Yutong Xie², Xixuan He¹, Yujing Ren¹, Chunhong Xue¹, Siqi Wang², Linrong Yuan², Miao Yu², Xuelin Cheng⁴, Xiaopan Li⁴, Sunfang Jiang⁴, Huirong Zhu¹

¹Tangqiao Community Health Service Center, Shanghai 200127, China. ²Shanghai University of Medicine and Health Sciences, Shanghai 201318, China. ³Shanghai DianJi University, Shanghai 201306, China. ⁴Health Man-agement Center, Zhongshan Hospital Affiliated to Fudan University, Shanghai 200032, China.*The authors contribute equally.

Address correspondence to: Sunfang Jiang, Health Management Center, Zhongshan Hospital Affiliated to Fudan University, Gate 5 East Campus, No. 179 Fenglin Road, Xuhui District, Shanghai 200032, China. Email: jiang.sunfang@zs-hospital.sh.cn. Huirong Zhu, Tangqiao Community Health Service Center, No.131 Pujian Road, Pudong New District, Shanghai 200127, China. Email: rachel1022@126.com.

DOI: https://doi.org/10.61189/568091unpkqk

Received May 11, 2024; Accepted July 16, 2024; Published September 30, 2024

Highlights

●This study collected three years of physical examination data from older adults in the Tangqiao community of Shanghai, which is more regionally representative.

●The most suitable model for this study was selected from six machine learning models to construct a fatty liver risk prediction model for the elderly.

●This study combines six feature selection algorithms with varying performance to screen the features most rele vant to fatty liver.

Mengying Zhan, Jiahao Zhang, Yuqiu Zhou, Qijun Xie, Fangfang Luo, Yu Zhou 

School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai  200093, China. 

Address correspondence to: Yu Zhou, School of Health Sciences and Engineering, University of  Shanghai for Science and Technology, No.516 Jungong Road, Shanghai 200093, China. Tel: +86- 18021042556. E-mail: zhouyu@usst.edu.cn.

DOI: https://doi.org/10.61189/650204jodubt 

Received January 29, 2024; Accepted March 25, 2024; Published September 30, 2024

Highlights

● The effect of electrode-tissue contact force on the efficacy and safety of ablation of atrial fibrillation was reviewed  in detail.

● The existing contact force sensing catheters on the market are compared and introduced.

● Three impedance-related methods for assessing catheter adherence are introduced.

Yichun Shen¹, Shuyi Wang¹, Yuhan Shen¹, Hua Xing²

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. ²Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai 200080, China.

Address correspondence to: Shuyi Wang, School of Health Science and Engineering, University of Shanghai for Science and Technology, NO.516, Jungong Road, Shanghai 200093, China. E-mail: wangshuyi@usst.edu.cn.

DOI: https://doi.org/10.61189/721472czacxf

Received April 12, 2024; Accepted July 11, 2024; Published September 30, 2024

Highlights

● Machine learning can enhance the individualization of treatment in Chinese massage.

● An intelligent system improves the efficiency of Traditional Chinese Medicine massage therapy.

● The integration of Traditional Chinese Medicine Massage Therapy with machine learning represents a new trend in future healthcare.

Weiwei Fan, Lin Mao, Bojun Liu, Chengli Song

Shanghai Institute for Minimally Invasive Therapy, School of Health Science and Engineering, University of Shanghai for Science and Technology, 200093, China.

Address correspondence to: Lin Mao, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Yangpu District, Shanghai 200093, China. Tel: +86-21-55572159. E-mail: linmao@usst.edu.cn.

DOI: https://doi.org/10.61189/883654uegazz

Received March 21, 2024; Accepted June 5, 2024; Published September 30, 2024

Highlights

● A V-shaped vascular clamp featuring a locking mechanism and transverse teeth has been developed.

● Comparative analysis of clamps with various inner diameters reveals optimal closure with specific configurations.

● The designed clamp presents superior stress-strain response, robust clamping force, and consistent corrosion resistance.

Yifei Bai, Rongguo Yan, Yuqing Yang, Chengang Mao

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Rongguo Yan, School of Health Sciences and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Shanghai 200093, China. E-mail: yanrongguo@usst.edu.cn.

DOI: https://doi.org/10.61189/846307fkxccq

Received April 12, 2024; Accepted July 11, 2024; Published September 30, 2024

Highlights

●The study evaluated five machine learning algorithms in analyzing urinary non-formed components. Among them, the Random Forests model demonstrated the highest accuracy, precision, recall, and F1 score, suggesting its effectiveness in analyzing urinary non-formed components.

●A technological innovation is introduced for home urinalysis, offering the potential to enhance medical efficiency and patient experience.

Yan Wang, Liwen Chen

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Liwen Chen, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Yangpu District, Shanghai 200093, China. E-mail: chenlw@usst.edu.cn.

DOI：https://doi.org/10.61189/974215qcjfzk

Highlights

● This paper presents a comprehensive review of the advancements in finite element analysis (FEA) within the field of prosthodontics over the past five years.● It examines the role of FEA in aiding the selection of restorative materials, enhancing prosthetic designs, and in vestigating the dynamic interactions between prostheses and natural dentition.● Integrating FEA findings with clinical practice enhances treatment outcomes and patient satisfaction.

Renling Zou¹, Yuhao Liu¹, Yicai Wu¹, Liang Zhao¹, Jigao Dai¹, Xiufang Hu¹, Xuezhi Yin² 

¹School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai, 200000, China. ²Shanghai Berry Electronic Technology Co., Ltd., Shanghai, 200000, China.

Address correspondence to: Renling Zou, School of Health Sciences and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Shanghai 200000, China. E-mail: zou renling@usst.edu.cn.

Acknowledgement: This work was supported by Science and Technology Commission of Shanghai Municipality (21S31906000), the National Natural Science Foundation of China (NSFC) Grant (61803265), and Medical-in dustrial cross-project of USST Grant (1022308524).

DOI: https://doi.org/10.61189/434505lacrsk

Received April 24, 2024; Accepted June 25, 2024; Published December 31, 2024 

Highlights 

 ● This study introduces a novel impedance model for the human upper limb, providing a highly accurate fit be tween frequency and impedance values. 

 ● The newly proposed Voltage Perception Threshold (VPT) method offers a more reliable measure of electrical stimulus sensation, independent of current magnitude and output frequency, compared to the traditional Current Perception Threshold (CPT).

Mingxia Wei, Qingyun Meng

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Qingyun Meng, School of Health Science and Engineering, University of Shanghai for Science and Technology, Yangpu District, Shanghai 200093, China. Tel: +86-13761813609. E-mail: mengqy@sumhs.edu.cn.

DOI: https://doi.org/10.61189/521889ygxkmc

Received May 15, 2024; Accepted June 25, 2024; Published December 31, 2024

Highlights

● A comprehensive overview of Visual-Inertial Navigation Systems.● Exploration of key technologies, including image processing methods for visual odometry.

Haonan Geng¹, Xudong Guo¹, Haibo Lin¹, Youguo Hao², Guojie Zhang³

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. ²Shanghai Putuo District People’s Hospital, Shanghai 200060, China. ³LingYuan Iron and Steel CO., LTD, Lingyuan 122500, Liaoning Province, China.

Address correspondence to: Xudong Guo, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Yangpu District, Shanghai 200093, China. Email: guoxd@usst.edu.cn; Youguo Hao, Shanghai Putuo District Central Hospital, No.1291 Jiangning Road, Putuo District, Shanghai, 200060, China. Email: youguohao6@163.com.

DOI: https://doi.org/10.61189/673672yizrwd

Received September 8, 2024; Accepted November 6, 2024; Published December 31,2024

Highlights

●Gait prediction relies on multimodal sensor data, and the acquisition of multimodal information, such as physical sensors and bioelectrical signal sensors, is introduced in order to monitor and analyze the lower limb movement in real time, and provide a data basis for prediction.● The application of machine learning algorithms in gait prediction technology, such as Support Vector Machine, Random Forest, and Back Propagation Neural Network, is reviewed to construct an optimized gait prediction model, which provides effective support for the intelligent control of exoskeleton.● Compared with machine learning algorithms, the article summarizes the researchers’ efforts to extract and un derstand the hidden patterns in gait data by constructing neural network models related to different deep learning algorithms, which are used to improve the accuracy and robustness of gait prediction.

Yibin Zhang¹, Yan Wang¹, Hongliu Yu²¹School of Medical Devices, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China. ²School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Address correspondence to: Hongliu Yu, School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai city Jungong road 516, Shanghai 200093, China. E-mail: yhl98@hotmail.com.

DOI：https://doi.org/10.61189/961030gznunx

Received June 21, 2024; Accepted November 20, 2024; Published December 31, 2024

Highlights

● In prosthetics, using AI algorithms to identify the fused sensor data as known walking patterns has extremely strong expandability. Moreover, as the learning data continues to expand, the robustness of the model itself also increases accordingly.● There are numerous AI algorithms currently available. The effective utilization of algorithm combination techniques to learn from each other’s strengths can significantly improve the accuracy of identification. The combined model of convolutional neural networks (CNN) and bidirectional long short term memory (LSTM) attempted in this paper has witnessed a significant improvement in its comprehensive recognition rate.● In the practical application of prosthetics, the real-time performance during the mode switching transition period is particularly important as it can reflect the flexibility of the prosthetics. In this paper, the algorithm optimized by the AI model has controlled the delay rate within one gait cycle, greatly enhancing the safety and reliability of pro-sthetics in actual use.