Head Impact Research Using Inertial Sensors in Sport: A Systematic Review of Methods, Demographics, and Factors Contributing to Exposure

Background Wearable devices and sensor technology provide objective, unbiased range of motion measurements that help health care professionals overcome the hindrances of protractor-based goniometry. This review aims to analyze the accuracy of existing wearable sensor technologies for hand range of motion measurement and identify the most accurate one. Methods We performed a systematic review by searching PubMed, CINAHL, and Embase for studies evaluating wearable sensor technology in hand range of motion assessment. Keywords used for the inquiry were related to wearable devices and hand goniometry. Results Of the 71 studies, 11 met the inclusion criteria. Ten studies evaluated gloves and 1 evaluated a wristband. The most common types of sensors used were bend sensors, followed by inertial sensors, Hall effect sensors, and magnetometers. Most studies compared wearable devices with manual goniometry, achieving optimal accuracy. Although most of the devices reached adequate levels of measurement error, accuracy evaluation in the reviewed studies might be subject to bias owing to the use of poorly reliable measurement techniques for comparison of the devices. Conclusion Gloves using inertial sensors were the most accurate. Future studies should use different comparison techniques, such as infrared camera–based goniometry or virtual motion tracking, to evaluate the performance of wearable devices.

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Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review

Sensors ◽

10.3390/s21155167 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5167

Author(s):

Nicky Baker ◽

Claire Gough ◽

Susan J. Gordon

Keyword(s):

Systematic Review ◽

Discriminant Validity ◽

Inertial Sensors ◽

Postural Sway ◽

Inertial Sensor ◽

Dynamic Balance ◽

Healthy Adults ◽

Gait Velocity ◽

Time Data ◽

Targeted Interventions

Compared to laboratory equipment inertial sensors are inexpensive and portable, permitting the measurement of postural sway and balance to be conducted in any setting. This systematic review investigated the inter-sensor and test-retest reliability, and concurrent and discriminant validity to measure static and dynamic balance in healthy adults. Medline, PubMed, Embase, Scopus, CINAHL, and Web of Science were searched to January 2021. Nineteen studies met the inclusion criteria. Meta-analysis was possible for reliability studies only and it was found that inertial sensors are reliable to measure static standing eyes open. A synthesis of the included studies shows moderate to good reliability for dynamic balance. Concurrent validity is moderate for both static and dynamic balance. Sensors discriminate old from young adults by amplitude of mediolateral sway, gait velocity, step length, and turn speed. Fallers are discriminated from non-fallers by sensor measures during walking, stepping, and sit to stand. The accuracy of discrimination is unable to be determined conclusively. Using inertial sensors to measure postural sway in healthy adults provides real-time data collected in the natural environment and enables discrimination between fallers and non-fallers. The ability of inertial sensors to identify differences in postural sway components related to altered performance in clinical tests can inform targeted interventions for the prevention of falls and near falls.

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Feasibility of using wearable inertial sensors for assessing gait changes after total knee arthroplasty: a systematic review and meta-analysis

Minerva Orthopedics ◽

10.23736/s2784-8469.21.04137-7 ◽

2021 ◽

Vol 72 (5) ◽

Author(s):

Alex MARTINO CINNERA ◽

Giovanni MORONE ◽

Serena MARRANO ◽

Giuseppe VANNOZZI ◽

Pietro PICERNO

Keyword(s):

Systematic Review ◽

Total Knee Arthroplasty ◽

Knee Arthroplasty ◽

Inertial Sensors ◽

Meta Analysis ◽

Total Knee ◽

Wearable Inertial Sensors

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Identification of Diseases Based on the Use of Inertial Sensors: A Systematic Review

Electronics ◽

10.3390/electronics9050778 ◽

2020 ◽

Vol 9 (5) ◽

pp. 778

Author(s):

Vasco Ponciano ◽

Ivan Miguel Pires ◽

Fernando Reinaldo Ribeiro ◽

Gonçalo Marques ◽

Maria Vanessa Villasana ◽

...

Keyword(s):

Machine Learning ◽

Systematic Review ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Inertial Sensors ◽

Automatic Recognition ◽

Learning Methods ◽

Less Invasive ◽

Machine Learning Methods ◽

The Future

Inertial sensors are commonly embedded in several devices, including smartphones, and other specific devices. This type of sensors may be used for different purposes, including the recognition of different diseases. Several studies are focused on the use of accelerometer signals for the automatic recognition of different diseases, and it may empower the different treatments with the use of less invasive and painful techniques for patients. This paper aims to provide a systematic review of the studies available in the literature for the automatic recognition of different diseases by exploiting accelerometer sensors. The most reliably detectable disease using accelerometer sensors, available in 54% of the analyzed studies, is the Parkinson’s disease. The machine learning methods implemented for the automatic recognition of Parkinson’s disease reported an accuracy of 94%. The recognition of other diseases is investigated in a few other papers, and it appears to be the target of further analysis in the future.

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The Use of Wearable Sensors in Human Movement Analysis in Non-Swimming Aquatic Activities: A Systematic Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16245067 ◽

2019 ◽

Vol 16 (24) ◽

pp. 5067

Author(s):

Daniel A. Marinho ◽

Henrique P. Neiva ◽

Jorge E. Morais

Keyword(s):

Systematic Review ◽

Aquatic Environment ◽

Web Of Science ◽

Inertial Sensors ◽

State Of The Art ◽

Wearable Sensors ◽

Movement Analysis ◽

Human Movement ◽

Dry Land ◽

Swimming Kinematics

The use of smart technology, specifically inertial sensors (accelerometers, gyroscopes, and magnetometers), to analyze swimming kinematics is being reported in the literature. However, little is known about the usage/application of such sensors in other human aquatic exercises. As the sensors are getting smaller, less expensive, and simple to deal with (regarding data acquisition), one might consider that its application to a broader range of exercises should be a reality. The aim of this systematic review was to update the state of the art about the framework related to the use of sensors assessing human movement in an aquatic environment, besides swimming. The following databases were used: IEEE Xplore, Pubmed, Science Direct, Scopus, and Web of Science. Five articles published in indexed journals, aiming to assess human exercises/movements in the aquatic environment were reviewed. The data from the five articles was categorized and summarized based on the aim, purpose, participants, sensor’s specifications, body area and variables analyzed, and data analysis and statistics. The analyzed studies aimed to compare the movement/exercise kinematics between environments (i.e., dry land versus aquatic), and in some cases compared healthy to pathological participants. The use of sensors in a rehabilitation/hydrotherapy perspective may provide major advantages for therapists.

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