Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy

Virtanen, Jaakko; Noponen, Tommi; Kotilahti, Kalle; Virtanen, Juha; Ilmoniemi, Risto J.

doi:10.1117/1.3606576

Cited by 79 publications

(80 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We introduced an automated accelerometer-based movement reduction algorithm (AMARA) that combines MARA, developed by our group [34], and integrated ideas from Virtanen et al [63]. Furthermore, AMARA adds new features to the artifact detection and reconstruction process.…”

Section: Algorithmmentioning

confidence: 99%

“…The subsequent steps, i.e., artifact detection, segmentation, and artifact removal, were adapted from MARA [34] and were improved. The reconstruction of the signal was specifically developed for long-term recordings (8−10 h) including a criterion adapted from ABAMAR [63]. The algorithm was developed for application in sleep studies, thus the parameters given (summarized in Table 1) are optimized for such long-term recordings.…”

Section: Algorithmmentioning

confidence: 99%

“…For MARA, the same MSD parameters were used as for AMARA. ABAMAR was implemented adopting the parameters given in [63] except for the motion detection threshold, which was set to 0.2-0.55 g/s in order to be better adapted to our measured data (g: earth's gravity). AMARA was applied to [O2Hb] and [HHb] time series.…”

Section: Validation Of Amara Against Human Scorers Mara and Abamarmentioning

confidence: 99%

“…Two methods have been published so far that used signals from acceleration sensors for MA removal [27,63]. The method presented by Izzetoglu et al [27] is based on a linear least square adaptive filter with an acceleration signal as a reference input signal.…”

Section: Introductionmentioning

confidence: 99%

“…The method presented by Izzetoglu et al [27] is based on a linear least square adaptive filter with an acceleration signal as a reference input signal. Virtanen et al [63] published a method ("accelerometer-based motion artifact removal", ABAMAR) where the acceleration changes (i.e., movements) were detected based on a threshold. MAs were defined only on changes in acceleration.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

et al. 2015

View full text Add to dashboard Cite

Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique ("acceleration-based movement artifact reduction algorithm", AMARA) is based on combining two methods: the "movement artifact reduction algorithm" (MARA, et al. Phys. Meas. 2010, 31, 649-662), and the "accelerometer-based motion artifact removal" (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.OPEN ACCESS Algorithms 2015, 8 1053 Scholkmann

show abstract

Section: Algorithmmentioning

confidence: 99%

Section: Algorithmmentioning

confidence: 99%

Section: Validation Of Amara Against Human Scorers Mara and Abamarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

et al. 2015

View full text Add to dashboard Cite

show abstract

A modelling study of a new malignant hyperthermia diagnosis device

Ricardez‐Sandoval

2015

Can J Chem Eng

View full text Add to dashboard Cite

This paper presents a mathematical model for better understanding of the functionality of a newly-proposed Malignant Hyperthermia (MH) diagnosis device. MH is a rare life-threatening condition that is usually triggered by exposure to certain drugs such as a volatile anesthetic agent, neuromuscular blocking agent, or succinylcholine. It is highly recommended to have this condition diagnosed immediately after its common symptoms appear. However, it is often only when the patient has had a severe or fatal reaction to anesthetic that a diagnosis is finally made. Due to this, many deaths have been reported before a patient has been diagnosed with this condition. Further for the diagnosis, the patients are subject to an expensive clinical diagnostic procedure and it is also necessary to continuously monitor the condition. In this study, a micro-total analysis system for MH diagnosis through the assessment of the end-tidal CO 2 concentration level that can also aid point-of-care testing is presented. Various model parameters of the system are considered and their effects on the behaviour of the system are assessed. The results presented in this study are based on the proposed mathematical model for the new MH diagnosis device and can be used to evaluate the device's functionality and performance prior to its manufacture.

show abstract

Ex vivo quantitative analysis of human corneal stroma dehydration by near‐infrared absorption spectroscopy

Sun

et al. 2019

Journal of Biophotonics

View full text Add to dashboard Cite

Corneal water content and hydrodynamics are critical indicators of eye health. In this work, a convenient method based on near‐infrared absorption spectroscopy (NIRA) was presented to measure the relative water content of the corneal stroma ex vivo, which paves the way to measure corneal water content in vivo. The relative water content of fresh corneal stroma during dehydration under natural conditions (temperature, 25.8 ± 0.3°C; humidity, 7.2% ± 0.9%) was monitored in real time, and the characteristic time τ when the relative water content dropped to 90% of the fresh corneal stroma was 140.1 ± 30.6 s. Furthermore, the change in the relative water content over time was found to be linear with a dehydration rate of 0.071% per second, consistent with indirect optical coherence pachymetry but with superior reproducibility and precision. Provided that the NIRA spectrometer is changed to a reflection structure from the current transmission configuration, the NIRA method proposed in this work has great potential for in vivo measurement with the advantages of non‐contact, high precision and low cost.

show abstract

Accelerometer-based method for correcting signal baseline changes caused by motion artifacts in medical near-infrared spectroscopy

Cited by 79 publications

References 22 publications

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

A modelling study of a new malignant hyperthermia diagnosis device

Ex vivo quantitative analysis of human corneal stroma dehydration by near‐infrared absorption spectroscopy

Contact Info

Product

Resources

About