Measurement of respiratory rate with inertial measurement units

Beck, Simon; Laufer, Bernhard; Krueger-Ziolek, Sabine; Möeller, Knut

doi:10.1515/cdbme-2020-3060

Cited by 15 publications

(19 citation statements)

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“…In [109], A. Shabeeb et al used an ADXL345 digital accelerometer interfaced with an Arduino UNO board to collect raw data concerning chest movement during breathing, passed to the LabVIEW platform for data processing and visualization. A Butterworth band-pass filter with 0.1 Hz low cut-off frequencies and 1 Hz high cut-off frequencies was applied to the collected raw data [109,110]. The derived signal was amplified 200 times; a Wavelet Analysis (WA) multiscale peak detection function was used.…”

Section: Overview Of Innovative Wearable Systems Based On Inertial Sensors To Monitor the Respiratory Activitymentioning

confidence: 99%

An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

et al. 2021

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The demand for wearable devices to measure respiratory activity is constantly growing, finding applications in a wide range of scenarios (e.g., clinical environments and workplaces, outdoors for monitoring sports activities, etc.). Particularly, the respiration rate (RR) is a vital parameter since it indicates serious illness (e.g., pneumonia, emphysema, pulmonary embolism, etc.). Therefore, several solutions have been presented in the scientific literature and on the market to make RR monitoring simple, accurate, reliable and noninvasive. Among the different transduction methods, the piezoresistive and inertial ones satisfactorily meet the requirements for smart wearable devices since unobtrusive, lightweight and easy to integrate. Hence, this review paper focuses on innovative wearable devices, detection strategies and algorithms that exploit piezoresistive or inertial sensors to monitor the breathing parameters. At first, this paper presents a comprehensive overview of innovative piezoresistive wearable devices for measuring user’s respiratory variables. Later, a survey of novel piezoresistive textiles to develop wearable devices for detecting breathing movements is reported. Afterwards, the state-of-art about wearable devices to monitor the respiratory parameters, based on inertial sensors (i.e., accelerometers and gyroscopes), is presented for detecting dysfunctions or pathologies in a non-invasive and accurate way. In this field, several processing tools are employed to extract the respiratory parameters from inertial data; therefore, an overview of algorithms and methods to determine the respiratory rate from acceleration data is provided. Finally, comparative analysis for all the covered topics are reported, providing useful insights to develop the next generation of wearable sensors for monitoring respiratory parameters.

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Section: Overview Of Innovative Wearable Systems Based On Inertial Sensors To Monitor the Respiratory Activitymentioning

confidence: 99%

An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

et al. 2021

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“…Therefore, there is need for further development of respiratory motion measurement technology, and in particular, the use of MEMS motion sensors has been investigated intensively in the recent years; for a selection of recent and notable papers on this subject, cf. [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Previous Workmentioning

confidence: 99%

“…Some ( [7][8][9][10]) articles consider only the use of a single accelerometer to estimate the breathing rate or the respiratory motion. More recent articles typically consider using an IMU which contains an accelerometer and a gyroscope ( [11][12][13][14][15][16]), or an accelerometer, a gyroscope and a magnetometer ( [6,17,18]). In addition to these, a method for estimating respiratory motion using only a magnet and a MEMS magnetic sensor is presented in [19].…”

Section: Previous Workmentioning

confidence: 99%

“…The number of MEMS sensors used form estimating respiratory motion varies between studies. Methods utilizing multiple IMU sensors apply common mode filtering [6,13,14,17,20], independent component analysis (ICA) [7], or a kinematic joint model [18] to achieve position independence or to mitigate motion artifacts during exercise.…”

Section: Previous Workmentioning

confidence: 99%

“…For example, if an IMU is attached to the chest of a subject, it is used to measure the changes of the thoracic angle according to the phase of the respiration cycle. Such a measurement is sufficient for estimating the breathing rate (including inspiratory and expiratory time) [6,13,17], flow waveform [7], and relative changes in tidal volume [14], but it cannot be used to measure the absolute position of the sensor in relation to a fixed zero level without additional assumptions (such as rigid joints in the sensor constellation [18]). In fact, to the best of the authors' knowledge, in the current literature there is only one article [11] besides this work, which has considered the estimation of absolute respiratory motion using a MEMS motion sensor.…”

Section: Previous Workmentioning

confidence: 99%

See 2 more Smart Citations

A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography

Lehtonen

Teuho

Koskinen

et al. 2021

Sensors

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We present a novel method for estimating respiratory motion using inertial measurement units (IMUs) based on microelectromechanical systems (MEMS) technology. As an application of the method we consider the amplitude gating of positron emission tomography (PET) imaging, and compare the method against a clinically used respiration motion estimation technique. The presented method can be used to detect respiratory cycles and estimate their lengths with state-of-the-art accuracy when compared to other IMU-based methods, and is the first based on commercial MEMS devices, which can estimate quantitatively both the magnitude and the phase of respiratory motion from the abdomen and chest regions. For the considered test group consisting of eight subjects with acute myocardial infarction, our method achieved the absolute breathing rate error per minute of 0.44 ± 0.23 1/min, and the absolute amplitude error of 0.24 ± 0.09 cm, when compared to the clinically used respiratory motion estimation technique. The presented method could be used to simplify the logistics related to respiratory motion estimation in PET imaging studies, and also to enable multi-position motion measurements for advanced organ motion estimation.

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Feasibility of Using Inertial Measurement Units (IMUs) to Augment Cadaveric Temporal Training

Wesson,

Ambike,

Patel

et al. 2024

The Laryngoscope

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ObjectiveInsertional speed of cochlear implant electrode arrays (EA) during surgery is correlated with force. Low insertional speed, and therefore force, may allow for preservation of intracochlear structures leading to improved outcomes. Given the importance of low insertional speeds, we investigate the feasibility of using inertial sensors for kinematic analysis during EA insertion to augment otolaryngology‐head and neck surgery training.MethodsPracticing otolaryngology surgeons were recruited and inertial measurement units (IMU; Metamotions+, MBIENTLAB Inc, San Jose, CA) consisting of accelerometers were used to measure hand speed during EA (Cochlear™Nucleus®CI522 cochlear implant with Slim Straight electrode, Cochlear Limited, Sydney, Australia) insertion into a cadaveric cochlea. A mixed regression model was utilized to determine differences in speed across trials within a surgeon.ResultsA total of nine trials were performed by three surgeons. The highest mean ± SD speed obtained was 8.4 ± 1.7 mm/s, and the highest speed was 22.5 mm/s. Mean speed was not significantly different across trials within surgeons (p > 0.05).DiscussionIMUs are relatively inexpensive and relatively easy to use sensors that provide information on variables that may be of interest for otolaryngology resident training. The use of IMUs as part of advanced temporal training for cochlear electrode insertion can provide insight into hand speed, thereby allowing residents to train with specific regard to this variable. Future randomized‐controlled trials can be carried out to determine whether IMUs are conducive to lower insertional speeds.Level of EvidenceNA Laryngoscope, 2024

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Measurement of respiratory rate with inertial measurement units

Cited by 15 publications

References 0 publications

An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

An Overview of Wearable Piezoresistive and Inertial Sensors for Respiration Rate Monitoring

A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography

Feasibility of Using Inertial Measurement Units (IMUs) to Augment Cadaveric Temporal Training

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