The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Physiological Measurement Handbook
Abstract
In order to understand the physiological measurements that play a part in urodynamics, it is helpful rst to consider the function of the healthy urinary tract. e urinary system has two distinct functions: the storage of urine for typically a period of hours 20.17.3 Bubbles 522 20.17.4 Rectal Activity 523 20.18 Complete Urodynamics System 523 20.18.1 Load Cell and Preamplier 523 20.18.2 Volume and Flow Circuitry 523 20.18.3 Pressure Circuitry 526 20.19 Adjuncts to Conventional Urodynamics 526 20.19.1 In Vitro Testing 526 20.19.1.1 Urine Dipstick Testing 526 20.19.1.2 Prostate-Specic Antigen 526 20.19.2 Simple Devices for Home Use 526 20.19.2.1 Frequency-Volume Chart 526 20.19.2.2 Leakage Diaper 526 20.19.3 Ultrasound 527 20.19.4 Ambulatory Urodynamics 527 20.19.5 Electromyography 529 20.19.6 Video Urodynamics (Cystography) 530 20.19.7 Cystoscopy 530 20.19.8 Urethral Pressure Prolometry 530 20.20 e Future 531 20.20.1 Home Uroowmetry 532 20.20.2 Noninvasive Measurement of Bladder Contractility 532 20.20.3 Indwelling Sensors 532 20.21 Equipment Suppliers 533 Acknowledgments 533 References 533 Bibliography 534 and the ecient and complete passage or voiding of urine at a socially convenient time. Symptoms of disrupted storage or voiding go under the generic term of lower urinary tract symptoms (LUTS). Many of the symptoms are common to a range of disease processes. Nevertheless, the literature makes a clear distinction between the symptoms and disease processes aecting storage and those that aect voiding.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Avolio, A. P., Butlin, M., & Walsh, A. (2010) · Physiological Measurement · doi:10.1088/0967-3334/31/1/r01 · Cited by 310
Cited by
Sharman, J. E., Avolio, A. P., Baulmann, J., Benetos, A., Blacher, J., Blizzard, C. L., Boutouyrie, P., Chen, C.-H., Chowienczyk, P., Cockcroft, J. R., et al. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehw632 · Cited by 231
Ha, T., Tran, J., Liu, S., Jang, H., Jeong, H., Mitbander, R., Huh, H., Qiu, Y., Duong, J., Wang, R. L., et al. (2019) · Advanced Science · doi:10.1002/advs.201900290 · Cited by 220
Heart sound classification from unsegmented phonocardiograms
Langley, P., & Murray, A. (2017) · Physiological Measurement · doi:10.1088/1361-6579/aa724c · Cited by 88
Le, K. H., Pham, H., Nguyen, T., Nguyen, T. A., Thanh, T., & Do, C. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.104963 · Cited by 77
Artificial intelligence from A to Z: From neural network to legal framework
van Assen, M., Lee, S., & Cecco, C. N. D. (2020) · European Journal of Radiology · doi:10.1016/j.ejrad.2020.109083 · Cited by 62
Automated Diagnosis of Heart Sounds Using Rule-Based Classification Tree
Karar, M. E., El-Khafif, S. H., & El-Brawany, M. A. (2017) · Journal of Medical Systems · doi:10.1007/s10916-017-0704-9 · Cited by 62
Automated signal quality assessment of mobile phone-recorded heart sound signals
Springer, D., Brennan, T. J., Ntusi, N., Abdelrahman, H. Y., Zuhlke, L. J., Mayosi, B. M., Tarassenko, L., & Clifford, G. D. (2016) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2016.1213902 · Cited by 46
Abnormal Heart Sounds Detected from Short Duration Unsegmented Phonocardiograms by Wavelet Entropy
Langley, P., & Murray, A. (2016) · Computing in cardiology · doi:10.22489/cinc.2016.156-268 · Cited by 33
Curriculum Implementation Facilitating and Hindering Factors: The Philippines Context
Palestina, R. L., Pangan, A. D., & Ancho, I. (2020) · International Journal of Education · doi:10.17509/ije.v13i2.25340 · Cited by 23
Critical Review of Uroflowmetry Methods
Alothmany, N., Mosli, H. A. M., Shokoueinejad, M., Alkashgari, R., Chiang, M., & Webster, J. G. (2018) · Journal of Medical and Biological Engineering · doi:10.1007/s40846-018-0375-0 · Cited by 21
Martínez, M. S., Ródenas, J., Rieta, J. J., & Alcaraz, R. (2019) · Physiological Measurement · doi:10.1088/1361-6579/ab2cb8 · Cited by 18
Ryu, J. S., Lee, S., Chu, Y., Ahn, M., Park, Y. J., & Yang, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0286916 · Cited by 17
Ng, K. A., Rusly, A., Gammad, G. G. L., Le, N., Liu, S.-C., Leong, K.-W., Zhang, M., Ho, J. S., Yoo, J., & Yen, S. (2020) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2020.3009088 · Cited by 14
Cai, T. Y., Haghighi, M. M., Roberts, P. A., Mervis, J., Qasem, A., Butlin, M., Celermajer, D. S., Avolio, A. P., Skilton, M. R., & Ayer, J. G. (2020) · American Journal of Hypertension · doi:10.1093/ajh/hpaa148 · Cited by 11
Video Voiding Device for Diagnosing Lower Urinary Tract Dysfunction in Men
Shokoueinejad, M., Alkashgari, R., Mosli, H. A. M., Alothmany, N., Levin, J. M., & Webster, J. G. (2017) · Journal of Medical and Biological Engineering · doi:10.1007/s40846-017-0283-8 · Cited by 8
Ryu, J. S., Lee, S., Chu, Y., Koh, S. B., Park, Y. J., Lee, J. Y., & Yang, S. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12082828 · Cited by 8
Embedded heart sounds and murmurs generator based on discrete wavelet transform
Karar, M. E., & El-Brawany, M. A. (2016) · International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC) · doi:10.1109/jec-ecc.2016.7518962 · Cited by 8
EMG instrumentation for educational physiotherapy research
Singh, A., Calixto, G. M., Felisbino, C. H. D., Zuffo, M. K., & Garay, J. R. B. (2016) · IEEE International Symposium on Consumer Electronics (ISCE) · doi:10.1109/isce.2016.7797390 · Cited by 4
Sebastián Rivera, R., & Anthony Marcotti, F. (2016) · Revista de otorrinolaringología y cirugía de cabeza y cuello · doi:10.4067/s0718-48162016000300004 · Cited by 4
PSoC-Based Embedded Instrumentation and Processing of sEMG Signals
Fezazi, M. E., Achmamad, A., Aqil, M., & Jbari, A. (2021) · Analog Integrated Circuits and Signal Processing · doi:10.1007/s10470-021-01850-x · Cited by 3
IoT system development for heart rhythm monitoring and cardiovascular risk estimation
Ríos, M. E. M., Golondrino, G. E. C., & Alarcón, M. A. O. (2024) · Eastern-European Journal of Enterprise Technologies · doi:10.15587/1729-4061.2024.299068 · Cited by 3
What Data Gathering Strategies Should I Use?
Cooksey, R., & Mcdonald, G. M. (2019) · Springer eBooks · doi:10.1007/978-981-13-7747-1_14 · Cited by 3
Biomedical Sensors and Data Acquisition
Gupta, R. (2019) · CRC Press eBooks · doi:10.1201/9780429113390-2 · Cited by 3
Electromyographic ( EMG ) Decomposition
Marateb, H. R., & McGill, K. C. (2016) · Wiley eBooks · doi:10.1002/047134608x.w8296 · Cited by 4
Validation of an algorithm to reveal the U wave in atrial fibrillation
Al-Karadi, M. S., Wilkinson, A. J., Caldwell, J., & Langley, P. (2018) · Scientific Reports · doi:10.1038/s41598-018-30493-8 · Cited by 2
FECG Extraction Using 1D Convolution Neural Network
Sharma, Y., Ray, S., & Yadav, O. P. (2021) · Algorithms for intelligent systems · doi:10.1007/978-981-16-1295-4_34 · Cited by 2
THE USE OF FLUID-FILLED CATHETERS AS REFERENCE BLOOD PRESSURE MONITORS
Mikhailov, Y., & Fabián, V. (2021) · Lékař a technika - Clinician and Technology · doi:10.14311/ctj.2021.1.01 · Cited by 1
How to Invent New Medical Devices
Webster, J. G. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512627
A Microcontroller-Based Heart Sounds and Murmurs Generator Using Discrete Wavelet Transform
Karar, M. E. (2016) · The International Conference on Electrical Engineering/The International Conference on Electrical Engineering · doi:10.21608/iceeng.2016.30259
Introduction to ECoG interfaces
Ha, S., Kim, C., Mercier, P. P., & Cauwenberghs, G. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-815115-0.00008-8
On the scaling properties of oscillatory modes with balanced energy
Dotov, D. G. (2022) · Frontiers in Network Physiology · doi:10.3389/fnetp.2022.974373
Pousti, R., Russell, D. M., Monroe, D. C., & Rhea, C. K. (2026) · Sensors · doi:10.3390/s26051719
Wubishet, M., Yinges, S. G., Meskel, T. G., Shimelis, B., & Mezgebu, E. (2026) · Discover Public Health · doi:10.1186/s12982-026-03032-4
Metadata
- Authors
- Drinnan, M., & Griffiths, C.
- Venue
- CRC Press eBooks
- Publisher
- CRC Press
- Published
- 2014-12-11
- OpenAlex
- W2884873657
- Cited by
- 34
- References
- 1
- Citations by year
- 2026: 2 · 2024: 1 · 2023: 3 · 2022: 1 · 2021: 3 · 2020: 5 · 2019: 5 · 2018: 3 · 2017: 3 · 2016: 8
- FWCI
- 8.41
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- CRC Press eBooks (publishedVersion)
- Digital Commons - Michigan Tech (Michigan Technological University) (submittedVersion)
- TeesRep (Teesside University) (submittedVersion)
- Topics
- Health Sciences › Medicine › Urology › Urinary Bladder and Prostate Research
- Health Sciences › Medicine › Urology › Pelvic floor disorders treatments
- Health Sciences › Medicine › Urology › Urinary Tract Infections Management
- Keywords
- urodynamics, lower urinary tract symptoms, bladder function, urinary voiding, bladder contractility, urethral pressure profilometry, cystoscopy, cystography, electromyography, ambulatory urodynamics, prostate-specific antigen, urine dipstick, frequency-volume chart
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
