Sensor-based technologies for motion analysis in sports injuries: a scoping review

被引:0
|
作者
Arzehgar, Afrooz [1 ]
Seyedhasani, Seyedeh Nahid [1 ]
Ahmadi, Fatemeh Baharvand [1 ]
Bagheri Baravati, Fatemeh [1 ]
Sadeghi Hesar, Alireza [1 ]
Kachooei, Amir Reza [2 ]
Aalaei, Shokoufeh [1 ,3 ]
机构
[1] Mashhad Univ Med Sci, Fac Med, Dept Med Informat, Mashhad, Iran
[2] AdventHlth, Rothman Orthopaed Florida, Orlando, FL USA
[3] Mashhad Univ Med Sci, Basic Sci Res Inst, Bioinformat Res Ctr, Mashhad, Iran
来源
BMC SPORTS SCIENCE MEDICINE AND REHABILITATION | 2025年 / 17卷 / 01期
关键词
Feedback; Injury; Motion analysis; Rehabilitation; Sensor; Sport; TIBIAL ROTATION; LOWER-LIMB; ANTERIOR; STABILITY; INTEGRATION; KINEMATICS; MOVEMENT; JOINT; TASK;
D O I
10.1186/s13102-025-01063-z
中图分类号
R49 [康复医学];
学科分类号
100215 ;
摘要
BackgroundInsightful motion analysis provides valuable information for athlete health, a crucial aspect of sports medicine. This systematic review presents an analytical overview of the use of various sensors in motion analysis for sports injury assessment.MethodsA comprehensive search of PubMed/MEDLINE, Scopus, and Web of Science was conducted in February 2024 using search terms related to "sport", "athlete", "sensor-based technology", "motion analysis", and "injury." Studies were included based on PCC (Participants, Concept, Context) criteria. Key data, including sensor types, motion data processing methods, injury and sport types, and application areas, were extracted and analyzed.ResultsForty-two studies met the inclusion criteria. Inertial measurement unit (IMU) sensors were the most commonly used for motion data collection. Sensor fusion techniques have gained traction, particularly for rehabilitation assessment. Knee injuries and joint sprains were the most frequently studied injuries, with statistical methods being the predominant approach to data analysis.ConclusionsThis review comprehensively explains sensor-based techniques in sports injury motion analysis. Significant research gaps, including the integration of advanced processing techniques, real-world applicability, and the inclusion of underrepresented domains such as adaptive sports, highlight opportunities for innovation. Bridging these gaps can drive the development of more effective, accessible, and personalized solutions in sports health.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Sensor-based prevention of falls and pressure ulcers: A scoping review
    Winkler, Anna
    Pallauf, Martin
    Krutter, Simon
    Kutschar, Patrick
    Osterbrink, Juergen
    Nestler, Nadja
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2025, 199
  • [2] A Novel Approach to Sensor-Based Motion Analysis for Sports: Piloting the Kabsch Algorithm in Volleyball and Handball
    Geisen, Mai
    Seifriz, Florian
    Fasold, Frowin
    Slupczynski, Michal
    Klatt, Stefanie
    IEEE SENSORS JOURNAL, 2024, 24 (21) : 35654 - 35663
  • [3] Sensor-based MIP technologies for targeted metabolomics analysis
    Ozcelikay, G.
    Kaya, S., I
    Ozkan, E.
    Cetinkaya, A.
    Nemutlu, E.
    Kir, S.
    Ozkan, S. A.
    TRAC-TRENDS IN ANALYTICAL CHEMISTRY, 2022, 146
  • [4] Sensor-based MIP technologies for targeted metabolomics analysis
    Ozcelikay, G.
    Kaya, S.I.
    Ozkan, E.
    Cetinkaya, A.
    Nemutlu, E.
    Kır, S.
    Ozkan, S.A.
    TrAC - Trends in Analytical Chemistry, 2022, 146
  • [5] Estimating the cost of sports injuries: A scoping review
    Turnbull, Matthew R.
    Gallo, Tania F.
    Carter, Hannah E.
    Drew, Michael
    Toohey, Liam A.
    Waddington, Gordon
    JOURNAL OF SCIENCE AND MEDICINE IN SPORT, 2024, 27 (05) : 307 - 313
  • [6] Sensor-Based Technologies in Sugarcane Agriculture
    Garcia, Angel Pontin
    Umezu, Claudio Kiyoshi
    Moriones Polania, Edna Carolina
    Dias Neto, Americo Ferraz
    Rossetto, Raffaella
    Albiero, Daniel
    SUGAR TECH, 2022, 24 (03) : 679 - 698
  • [7] Sensor-Based Additive Manufacturing Technologies
    Mahale, Rayappa Shrinivas
    Vasanth, Shamanth
    Krishna, Hemanth
    Chikkegouda, Sharath Peramenahalli
    Rajendrachari, Shashanka
    Patil, Adarsh
    Rathod, Babarao Sitaram
    BIOINTERFACE RESEARCH IN APPLIED CHEMISTRY, 2022, 12 (03): : 3513 - 3521
  • [8] Sensor-Based Technologies in Sugarcane Agriculture
    Angel Pontin Garcia
    Claudio Kiyoshi Umezu
    Edna Carolina Moriones Polania
    Américo Ferraz Dias Neto
    Raffaella Rossetto
    Daniel Albiero
    Sugar Tech, 2022, 24 : 679 - 698
  • [9] Wearable Motion Sensor Based Analysis of Swing Sports
    Anand, Akash
    Sharma, Manish
    Srivastava, Rupika
    Kaligounder, Lakshmi
    Prakash, Divya
    2017 16TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA), 2017, : 261 - 267
  • [10] Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review
    Huang, Xinxin
    Xue, Yunan
    Ren, Shuyun
    Wang, Fei
    SENSORS, 2023, 23 (22)