1
|
Hurtado-Perez AE, Toledano-Ayala M, Cruz-Albarran IA, Lopez-Zúñiga A, Moreno-Perez JA, Álvarez-López A, Rodriguez-Resendiz J, Perez-Ramirez CA. Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis. Biomimetics (Basel) 2025; 10:339. [PMID: 40422169 DOI: 10.3390/biomimetics10050339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2025] [Revised: 05/08/2025] [Accepted: 05/13/2025] [Indexed: 05/28/2025] Open
Abstract
This review provides an in-depth examination of the technologies and methods used for the acquisition and processing of kinetic and kinematic variables in human motion analysis. This review analyzes the capabilities and limitations of motion-capture cameras (MCCs), inertial measurement units (IMUs), force platforms, and other prototype technologies. The role of advanced processing techniques, including filtering and transformation methods, and the increasing integration of artificial intelligence (AI) and machine learning (ML) for data classification is also discussed. These advancements enhance the precision and efficiency of biomechanical analyses, paving the way for more accurate assessments of human movement patterns. The review concludes by providing guidelines for the effective application of these technologies in both clinical and research settings, emphasizing the need for comprehensive validation to ensure reliability. This comprehensive overview serves as a valuable resource for researchers and professionals in the field of biomechanics, guiding the selection and application of appropriate technologies and methodologies for human movement analysis.
Collapse
Affiliation(s)
- Andres Emilio Hurtado-Perez
- Division de Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Cerro de las Campanas S/N, Querétaro 76010, Mexico
| | - Manuel Toledano-Ayala
- Division de Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Cerro de las Campanas S/N, Querétaro 76010, Mexico
- Tequexquite, Centro de Investigación y Desarrollo Tecnológico para la Accesibilidad e Innovación Social, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Campus Aeropuerto, Carretera a Chichimequillas S/N, Ejido Bolaños, Querétaro 76140, Mexico
| | - Irving A Cruz-Albarran
- C.A. Sistemas de Inteligencia Artificial Aplicados a Modelos Biomédicos y Mecánicos, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Campus San Juan del Rio, Rio Moctezuma 249, Col. San Cayetano, San Juan del Río 76807, Mexico
| | - Alejandra Lopez-Zúñiga
- Tequexquite, Centro de Investigación y Desarrollo Tecnológico para la Accesibilidad e Innovación Social, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Campus Aeropuerto, Carretera a Chichimequillas S/N, Ejido Bolaños, Querétaro 76140, Mexico
| | - Jesús Adrián Moreno-Perez
- Division de Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Cerro de las Campanas S/N, Querétaro 76010, Mexico
- Tequexquite, Centro de Investigación y Desarrollo Tecnológico para la Accesibilidad e Innovación Social, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Campus Aeropuerto, Carretera a Chichimequillas S/N, Ejido Bolaños, Querétaro 76140, Mexico
| | - Alejandra Álvarez-López
- Division de Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Cerro de las Campanas S/N, Querétaro 76010, Mexico
| | - Juvenal Rodriguez-Resendiz
- Division de Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Cerro de las Campanas S/N, Querétaro 76010, Mexico
| | - Carlos A Perez-Ramirez
- Tequexquite, Centro de Investigación y Desarrollo Tecnológico para la Accesibilidad e Innovación Social, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Campus Aeropuerto, Carretera a Chichimequillas S/N, Ejido Bolaños, Querétaro 76140, Mexico
- C.A. Sistemas de Inteligencia Artificial Aplicados a Modelos Biomédicos y Mecánicos, Facultad de Ingeniería, Universidad Autónoma de Querétaro, Campus Aeropuerto, Carretera a Chichimequillas S/N, Ejido Bolaños, Querétaro 76140, Mexico
| |
Collapse
|
2
|
Tajitsu Y, Takarada J, Hikichi T, Sugii R, Takatani K, Yanagimoto H, Nakanishi R, Shiomi S, Kitamoto D, Nakiri T, Takeuchi O, Deguchi M, Muto T, Kuroki K, Amano W, Misumi A, Takahashi M, Sugiyama K, Tanabe A, Kamohara S, Nisho R, Takeshita K. Application of Piezoelectric PLLA Braided Cord as Wearable Sensor to Realize Monitoring System for Indoor Dogs with Less Physical or Mental Stress. MICROMACHINES 2023; 14:143. [PMID: 36677204 PMCID: PMC9865504 DOI: 10.3390/mi14010143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 12/29/2022] [Accepted: 01/03/2023] [Indexed: 06/17/2023]
Abstract
We attempted to realize a prototype system that monitors the living condition of indoor dogs without physical or mental burden by using a piezoelectric poly-l-lactic acid (PLLA) braided cord as a wearable sensor. First, to achieve flexibility and durability of the piezoelectric PLLA braided cord used as a sensor for indoor dogs, the process of manufacturing the piezoelectric PLLA fiber for the piezoelectric braided cord was studied in detail and improved to achieve the required performance. Piezoelectric PLLA braided cords were fabricated from the developed PLLA fibers, and the finite element method was used to realize an e-textile that can effectively function as a monitoring sensor. As a result, we realized an e-textile that feels similar to a high-grade textile and senses the complex movements of indoor dogs without the use of a complex computer system. Finally, a prototype system was constructed and applied to an actual indoor dog to demonstrate the usefulness of the e-textile as a sensor for indoor dog monitoring.
Collapse
Affiliation(s)
- Yoshiro Tajitsu
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Jun Takarada
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Tokiya Hikichi
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Ryoji Sugii
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Kohei Takatani
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Hiroki Yanagimoto
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Riku Nakanishi
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Seita Shiomi
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Daiki Kitamoto
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Takuo Nakiri
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Osamu Takeuchi
- Electrical Engineering Department, Graduate School of Science and Engineering, Kansai University, Suita 5640-8680, Japan
| | - Miki Deguchi
- Tokyo IoT Technology Department, 5G & IoT Engineering Division, Softbank Co., Kaigan, Tokyo 105-7529, Japan
| | - Takanori Muto
- Tokyo IoT Technology Department, 5G & IoT Engineering Division, Softbank Co., Kaigan, Tokyo 105-7529, Japan
| | - Kazuaki Kuroki
- Tokyo IoT Technology Department, 5G & IoT Engineering Division, Softbank Co., Kaigan, Tokyo 105-7529, Japan
| | - Wataru Amano
- Tokyo IoT Technology Department, 5G & IoT Engineering Division, Softbank Co., Kaigan, Tokyo 105-7529, Japan
| | - Ayaka Misumi
- Tokyo IoT Technology Department, 5G & IoT Engineering Division, Softbank Co., Kaigan, Tokyo 105-7529, Japan
| | | | | | - Akira Tanabe
- Renesas Electronics Co., Ltd., Toyosu, Tokyo 135-0061, Japan
| | - Shiro Kamohara
- Renesas Electronics Co., Ltd., Toyosu, Tokyo 135-0061, Japan
| | - Rei Nisho
- Teijin Frontier Co., Ltd., Kita, Osaka 530-8605, Japan
| | | |
Collapse
|
3
|
Zeng X, Deng HT, Wen DL, Li YY, Xu L, Zhang XS. Wearable Multi-Functional Sensing Technology for Healthcare Smart Detection. MICROMACHINES 2022; 13:254. [PMID: 35208378 PMCID: PMC8874439 DOI: 10.3390/mi13020254] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 01/30/2022] [Accepted: 01/31/2022] [Indexed: 11/21/2022]
Abstract
In recent years, considerable research efforts have been devoted to the development of wearable multi-functional sensing technology to fulfill the requirements of healthcare smart detection, and much progress has been achieved. Due to the appealing characteristics of flexibility, stretchability and long-term stability, the sensors have been used in a wide range of applications, such as respiration monitoring, pulse wave detection, gait pattern analysis, etc. Wearable sensors based on single mechanisms are usually capable of sensing only one physiological or motion signal. In order to measure, record and analyze comprehensive physical conditions, it is indispensable to explore the wearable sensors based on hybrid mechanisms and realize the integration of multiple smart functions. Herein, we have summarized various working mechanisms (resistive, capacitive, triboelectric, piezoelectric, thermo-electric, pyroelectric) and hybrid mechanisms that are incorporated into wearable sensors. More importantly, to make wearable sensors work persistently, it is meaningful to combine flexible power units and wearable sensors and form a self-powered system. This article also emphasizes the utility of self-powered wearable sensors from the perspective of mechanisms, and gives applications. Furthermore, we discuss the emerging materials and structures that are applied to achieve high sensitivity. In the end, we present perspectives on the outlooks of wearable multi-functional sensing technology.
Collapse
Affiliation(s)
- Xu Zeng
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; (X.Z.); (H.-T.D.); (D.-L.W.); (Y.-Y.L.)
| | - Hai-Tao Deng
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; (X.Z.); (H.-T.D.); (D.-L.W.); (Y.-Y.L.)
| | - Dan-Liang Wen
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; (X.Z.); (H.-T.D.); (D.-L.W.); (Y.-Y.L.)
| | - Yao-Yao Li
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; (X.Z.); (H.-T.D.); (D.-L.W.); (Y.-Y.L.)
| | - Li Xu
- Rehabilitation Department, Sichuan Provincial People’s Hospital, Chengdu 610072, China
| | - Xiao-Sheng Zhang
- School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; (X.Z.); (H.-T.D.); (D.-L.W.); (Y.-Y.L.)
| |
Collapse
|
4
|
Frediani G, Vannetti F, Bocchi L, Zonfrillo G, Carpi F. Monitoring Flexions and Torsions of the Trunk via Gyroscope-Calibrated Capacitive Elastomeric Wearable Sensors. SENSORS 2021; 21:s21206706. [PMID: 34695926 PMCID: PMC8539866 DOI: 10.3390/s21206706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/01/2021] [Accepted: 10/04/2021] [Indexed: 11/16/2022]
Abstract
Reliable, easy-to-use, and cost-effective wearable sensors are desirable for continuous measurements of flexions and torsions of the trunk, in order to assess risks and prevent injuries related to body movements in various contexts. Piezo-capacitive stretch sensors, made of dielectric elastomer membranes coated with compliant electrodes, have recently been described as a wearable, lightweight and low-cost technology to monitor body kinematics. An increase of their capacitance upon stretching can be used to sense angular movements. Here, we report on a wearable wireless system that, using two sensing stripes arranged on shoulder straps, can detect flexions and torsions of the trunk, following a simple and fast calibration with a conventional tri-axial gyroscope on board. The piezo-capacitive sensors avoid the errors that would be introduced by continuous sensing with a gyroscope, due to its typical drift. Relative to stereophotogrammetry (non-wearable standard system for motion capture), pure flexions and pure torsions could be detected by the piezo-capacitive sensors with a root mean square error of ~8° and ~12°, respectively, whilst for flexion and torsion components in compound movements, the error was ~13° and ~15°, respectively.
Collapse
Affiliation(s)
- Gabriele Frediani
- Department of Industrial Engineering, University of Florence, 50121 Florence, Italy; (G.F.); (G.Z.)
| | | | - Leonardo Bocchi
- Department of Information Engineering, University of Florence, 50121 Florence, Italy;
| | - Giovanni Zonfrillo
- Department of Industrial Engineering, University of Florence, 50121 Florence, Italy; (G.F.); (G.Z.)
| | - Federico Carpi
- Department of Industrial Engineering, University of Florence, 50121 Florence, Italy; (G.F.); (G.Z.)
- IRCCS Fondazione don Carlo Gnocchi ONLUS, 50143 Florence, Italy;
- Correspondence:
| |
Collapse
|