A Hybrid Motion Capture Helmet System for Measuring the Kinematic Parameters of Gait

Volf, Petr; Hejda, Jan; Kutílek, Patrik; Sourek, Jakub; Hozman, Jiřı́

doi:10.1109/tsp.2018.8441372

Cited by 2 publications

(4 citation statements)

References 19 publications

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“…When navigating automatically, they can be used for vehicles, vessels, missiles, and aircraft for accurate positioning and operational status monitoring. [147,162,163] J. Tian et al applied fiber accelerometers to high-accuracy and high-fast control Figure 50. The miniaturization of the optical interferometric accelerometers.…”

Section: Intelligent Control and Safety Monitoringmentioning

confidence: 99%

“…When navigating automatically, they can be used for vehicles, vessels, missiles, and aircraft for accurate positioning and operational status monitoring. [ 147,162,163 ] J. Tian et al. applied fiber accelerometers to high‐accuracy and high‐fast control systems to obtain acceleration signals for the control process and transmit them to the controller for fast steering mirror control ( Figure b).…”

Section: Applications Of Optical Interferometric Mems Accelerometermentioning

confidence: 99%

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Optical Interferometric MEMS Accelerometers

Zhao,

Qi,

Wang

et al. 2023

Laser & Photonics Reviews

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Laser interferometry is one of the most accurate measurement technologies whose displacement resolution can reach the femtometer (fm) level. With the development of Micro‐Electro‐Mechanical Systems(MEMS) technology, many excellent optical interferometric MEMS sensors have emerged, which play an essential role in intelligent manufacturing, aerospace, and many other fields. Among them, optical interferometric MEMS accelerometers develop rapidly due to their high sensitivity, low noise, and anti‐electromagnetic interference advantages. Lots of research in optical interferometric chip design, micro‐nano fabrication process, signal demodulation algorithm, and range extension technology are performed, and different types of MEMS accelerometers based on the optical interferometric principles are developed, which have been demonstrated and applied in the fields of disaster monitoring, equipment operation and maintenance, and resource exploration. This paper reviews the development status of optical interferometric MEMS accelerometers, mainly focusing on the critical problems and solutions that need to be solved in the development process of optical interferometric accelerometers, and finally introduces the typical application scenarios.

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Section: Intelligent Control and Safety Monitoringmentioning

confidence: 99%

“…When navigating automatically, they can be used for vehicles, vessels, missiles, and aircraft for accurate positioning and operational status monitoring. [ 147,162,163 ] J. Tian et al. applied fiber accelerometers to high‐accuracy and high‐fast control systems to obtain acceleration signals for the control process and transmit them to the controller for fast steering mirror control ( Figure b).…”

Section: Applications Of Optical Interferometric Mems Accelerometermentioning

confidence: 99%

Optical Interferometric MEMS Accelerometers

Zhao,

Qi,

Wang

et al. 2023

Laser & Photonics Reviews

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“…In the case of lower acquisition frequency, around 10-20 Hz, the proposed studies focused on determining head motion patterns, which has applicability in medical fields [28,40]. The most common acquisition frequency was observed to be within a range of 48 Hz to 100 Hz, with diverse applicability (general HCI solutions, physical and mental activity analyses, sports training, and medical) [23,36,41,42,47,62,[64][65][66]. Another range which we determined had been used in the papers reviewed was an acquisition frequency of 120 Hz to 48 kHz.…”

Section: Head Motion Systemsmentioning

confidence: 99%

“…Another point is related to the size of the trainable datasets. In this study, we observed that the number of participants involved in data acquisition varied between 1 person [28,65] and 63 people [36]. Regarding the range of age, there was a wide variation in the age of volunteers who took part in each experiment In Figure 7, the rest of the papers (indicated by Other) used other computational models or provided improvements to the DLM or CML architecture.…”

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confidence: 99%

Using Inertial Sensors to Determine Head Motion—A Review

Severin

Dobrea

2021

J. Imaging

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Human activity recognition and classification are some of the most interesting research fields, especially due to the rising popularity of wearable devices, such as mobile phones and smartwatches, which are present in our daily lives. Determining head motion and activities through wearable devices has applications in different domains, such as medicine, entertainment, health monitoring, and sports training. In addition, understanding head motion is important for modern-day topics, such as metaverse systems, virtual reality, and touchless systems. The wearability and usability of head motion systems are more technologically advanced than those which use information from a sensor connected to other parts of the human body. The current paper presents an overview of the technical literature from the last decade on state-of-the-art head motion monitoring systems based on inertial sensors. This study provides an overview of the existing solutions used to monitor head motion using inertial sensors. The focus of this study was on determining the acquisition methods, prototype structures, preprocessing steps, computational methods, and techniques used to validate these systems. From a preliminary inspection of the technical literature, we observed that this was the first work which looks specifically at head motion systems based on inertial sensors and their techniques. The research was conducted using four internet databases—IEEE Xplore, Elsevier, MDPI, and Springer. According to this survey, most of the studies focused on analyzing general human activity, and less on a specific activity. In addition, this paper provides a thorough overview of the last decade of approaches and machine learning algorithms used to monitor head motion using inertial sensors. For each method, concept, and final solution, this study provides a comprehensive number of references which help prove the advantages and disadvantages of the inertial sensors used to read head motion. The results of this study help to contextualize emerging inertial sensor technology in relation to broader goals to help people suffering from partial or total paralysis of the body.

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A Hybrid Motion Capture Helmet System for Measuring the Kinematic Parameters of Gait

Cited by 2 publications

References 19 publications

Optical Interferometric MEMS Accelerometers

Optical Interferometric MEMS Accelerometers

Using Inertial Sensors to Determine Head Motion—A Review

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