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Ali RT, Abdullah TN, Emin AK. The effectiveness of two types of low-level laser therapy in patients with persistent tinnitus. Lasers Med Sci 2023; 38:132. [PMID: 37273123 DOI: 10.1007/s10103-023-03797-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 05/08/2023] [Indexed: 06/06/2023]
Abstract
Tinnitus is a perception disorder of sound with no hearing impulse. It is a very common otology complaint that leads to worsening quality of life. The experience of sound is only the product of neural system activity, with no matching mechanical or vibratory activity in the cochlea, and is unrelated to any external stimuli. Low-level laser therapy (LLLT) is a medical treatment of tinnitus that uses low-energy-level lasers or light-emitting diodes to stimulate or inhibit cellular function. The study included nine patients aged 20-68 years with unilateral or bilateral tinnitus. It was a self-controlled clinical trial study on subjective tinnitus. All patients attended the ENT outpatient Department, Rzgari Teaching Hospital, Erbil, Iraq. Two types of low-level laser therapy (LLLT) devices were used for patients. The first tool, a soft laser called a Tinnitool, has a wavelength of 660 nm and a power of 100 mW. The second tool is a Tinnitus Pen, which has a wavelength of 650 nm and a power of 5 mW. Seven females (77.7%) and two males (22.2%) participated in this study during one month. The mean age of the study sample was 44 years, with a standard deviation of 15.59 years. There was a significant improvement in the comparison of both types of therapy low-level laser before and after treatment, which reduced the tinnitus level among patients from 70% before treatment to 59% and 65.50%, respectively, after one month of treatment. A paired t test was applied to assess this difference before and after treatment. LLLT devices can be an effective device tool for the treatment of tinnitus and can reduce the symptoms of annoyance that affect the life of the sufferer.
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Affiliation(s)
- Ronak Taher Ali
- Department of Pharmacology & Medical Physics, Collage of Medicine, Hawler Medical University, Kurdistan Region Government, Erbil, Iraq.
- Department of Physiotherapy, Faculty of Applied Science, Tishk International University, Erbil, Kurdistan Region Government, Iraq.
| | - Tara Nooruldeen Abdullah
- Department of Pharmacology & Medical Physics, Collage of Medicine, Hawler Medical University, Kurdistan Region Government, Erbil, Iraq
| | - Abdulkhaliq K Emin
- Surgical Department, Collage of Medicine, Hawler Medical University, Kurdistan Region Government, Erbil, Iraq
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Searchfield GD, Sanders PJ, Doborjeh Z, Doborjeh M, Boldu R, Sun K, Barde A. A State-of-Art Review of Digital Technologies for the Next Generation of Tinnitus Therapeutics. Front Digit Health 2021; 3:724370. [PMID: 34713191 PMCID: PMC8522011 DOI: 10.3389/fdgth.2021.724370] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 07/12/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Digital processing has enabled the development of several generations of technology for tinnitus therapy. The first digital generation was comprised of digital Hearing Aids (HAs) and personal digital music players implementing already established sound-based therapies, as well as text based information on the internet. In the second generation Smart-phone applications (apps) alone or in conjunction with HAs resulted in more therapy options for users to select from. The 3rd generation of digital tinnitus technologies began with the emergence of many novel, largely neurophysiologically-inspired, treatment theories that drove development of processing; enabled through HAs, apps, the internet and stand-alone devices. We are now of the cusp of a 4th generation that will incorporate physiological sensors, multiple transducers and AI to personalize therapies. Aim: To review technologies that will enable the next generations of digital therapies for tinnitus. Methods: A "state-of-the-art" review was undertaken to answer the question: what digital technology could be applied to tinnitus therapy in the next 10 years? Google Scholar and PubMed were searched for the 10-year period 2011-2021. The search strategy used the following key words: "tinnitus" and ["HA," "personalized therapy," "AI" (and "methods" or "applications"), "Virtual reality," "Games," "Sensors" and "Transducers"], and "Hearables." Snowballing was used to expand the search from the identified papers. The results of the review were cataloged and organized into themes. Results: This paper identified digital technologies and research on the development of smart therapies for tinnitus. AI methods that could have tinnitus applications are identified and discussed. The potential of personalized treatments and the benefits of being able to gather data in ecologically valid settings are outlined. Conclusions: There is a huge scope for the application of digital technology to tinnitus therapy, but the uncertain mechanisms underpinning tinnitus present a challenge and many posited therapeutic approaches may not be successful. Personalized AI modeling based on biometric measures obtained through various sensor types, and assessments of individual psychology and lifestyles should result in the development of smart therapy platforms for tinnitus.
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Affiliation(s)
- Grant D. Searchfield
- Section of Audiology, The University of Auckland, Auckland, New Zealand
- Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Philip J. Sanders
- Section of Audiology, The University of Auckland, Auckland, New Zealand
- Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Zohreh Doborjeh
- Section of Audiology, The University of Auckland, Auckland, New Zealand
- Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Maryam Doborjeh
- School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
| | - Roger Boldu
- Augmented Human Laboratory, Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Kevin Sun
- Section of Audiology, The University of Auckland, Auckland, New Zealand
| | - Amit Barde
- Empathic Computing Laboratory, Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
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