{"id":977,"date":"2017-03-31T06:27:06","date_gmt":"2017-03-31T06:27:06","guid":{"rendered":"http:\/\/bear-hearing.dk\/?page_id=977"},"modified":"2019-03-29T13:37:25","modified_gmt":"2019-03-29T13:37:25","slug":"tobias-piechowiak","status":"publish","type":"page","link":"https:\/\/bear-hearing.dk\/da\/whoweare\/tobias-piechowiak\/","title":{"rendered":"Tobias Piechowiak \u2013 Hvem vi er"},"content":{"rendered":"

Hvem vi er<\/h3>\t\t\t
Projektet havde deltagelse af en gruppe dedikerede mennesker, der kom fra audiologiske klinikker, universiteter, teknologisk service, og h\u00f8reapparatindustrien. Det var medicinske audiologer og otologer, ingeni\u00f8rer, konsulenter og audiologop\u00e6der. Nogle unge, andre mere erfarne. Nogle arbejdede p\u00e5 projektet p\u00e5 fuld tid, andre p\u00e5 deltid og med andre forpligtelser. Enkelte havde direkte erfaringer med h\u00f8reneds\u00e6ttelse og rehabilitering.<\/div>\n\t\t<\/div><\/div><\/div>
<\/div><\/div><\/div>
\n\n
\n\t\"Tobias\n<\/div>\n\n<\/div><\/div><\/div>
\n
\n\t

Tobias Piechowiak<\/b><\/a><\/div>\r\nSeniorforsker\r\nGN Resound<\/h4>\n<\/div>\n<\/div><\/div><\/div><\/div>

Tobias Piechowiak<\/h3>\n
\n\t

Tobias Piechowiak fik sine B.E. og M.Sc. grader fra Oldenburg Universitet, Tyskland i 2005. I 2009 fik han sin PhD grad i auditiv signal processing fra Danmarks Tekniske Universitet, finansieret af den danske stat. Siden 2010 har han arbejdet som forsker i R&D afdelingen ved GN Resound A\/S. Hans forskningsinteresser inkluderer bilateral signal behandling i h\u00f8reapparater, computational auditory models, og anvendelsen af data mining og machine learning metoder med henblik p\u00e5 forbedringer i h\u00f8reapparats algoritmerne.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div>

Arbejdsomr\u00e5de<\/h3>\n
\n\t

Tobias Piechowiak bidrager med erfaring indenfor h\u00f8reapparater, signalbehandling og dataanalyse.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

Ressourcer<\/h3>\n
\n\t<\/div>\n<\/div><\/div>
\n
\n\t

Publikationer<\/h4>\n
<\/a><\/form>\r\n \r\n \r\n
\r\n

2022<\/h3>\r\n <\/td>\r\n <\/tr>

Sanchez-Lopez, Raul; Wu, Mengfan; Fereczkowski, Michal; Santurette, S\u00e9bastien; Baumann, Monika; Kowalewski, Borys; Piechowiak, Tobias; Bisgaard, Nikolai; Ravn, Gert; Narayanan, Sreeram Kaithali; Dau, Torsten; Neher, Tobias<\/p>

Towards Auditory Profile-Based Hearing-Aid Fittings: BEAR Rationale and Clinical Implementation<\/a> Journal Article<\/span> <\/p>

Audiological Research, <\/span>12 <\/span>(5), <\/span>pp. 564-573, <\/span>2022<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{AudRes2022a,
\r\ntitle = {Towards Auditory Profile-Based Hearing-Aid Fittings: BEAR Rationale and Clinical Implementation},
\r\nauthor = {Raul Sanchez-Lopez and Mengfan Wu and Michal Fereczkowski and S\u00e9bastien Santurette and Monika Baumann and Borys Kowalewski and Tobias Piechowiak and Nikolai Bisgaard and Gert Ravn and Sreeram Kaithali Narayanan and Torsten Dau and Tobias Neher},
\r\nurl = {https:\/\/doi.org\/10.3390\/audiolres12050055},
\r\ndoi = {10.3390\/audiolres12050055},
\r\nyear = {2022},
\r\ndate = {2022-10-09},
\r\njournal = {Audiological Research},
\r\nvolume = {12},
\r\nnumber = {5},
\r\npages = {564-573},
\r\nabstract = {(1) Background: To improve hearing-aid rehabilitation, the Danish \u2018Better hEAring Rehabilitation\u2019 (BEAR) project recently
\r\ndeveloped methods for individual hearing loss
\r\ncharacterization and hearing-aid fitting. Four auditory profiles differing in terms of audiometric hearing loss and supra-threshold hearing abilities were identified. To enable auditory profile-based hearing-aid treatment, a fitting rationale leveraging differences in gain prescription and signal-to- noise (SNR) improvement was developed. This report describes the translation of this rationale to clinical devices supplied by three industrial partners. (2) Methods: Regarding the SNR improvement, advanced feature settings were proposed and verified based on free-field measurements made with an acoustic mannikin fitted with the different hearing aids. Regarding the gain prescription, a clinically feasible fitting tool and procedure based on real-ear gain adjustments were developed. (3) Results: Analyses of the collected real-ear gain and SNR improvement data confirmed the feasibility of the clinical implementation. Differences between the auditory profile-based fitting strategy and a current \u2018best practice\u2019 procedure based on the NAL- NL2 fitting rule were verified and are discussed in terms of limitations and future perspectives. (4) Conclusion: Based on a joint effort from academic and industrial partners, the BEAR fitting rationale was transferred to commercially available hearing aids.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/div>

Close<\/a><\/p><\/div>

(1) Background: To improve hearing-aid rehabilitation, the Danish \u2018Better hEAring Rehabilitation\u2019 (BEAR) project recently
\r\ndeveloped methods for individual hearing loss
\r\ncharacterization and hearing-aid fitting. Four auditory profiles differing in terms of audiometric hearing loss and supra-threshold hearing abilities were identified. To enable auditory profile-based hearing-aid treatment, a fitting rationale leveraging differences in gain prescription and signal-to- noise (SNR) improvement was developed. This report describes the translation of this rationale to clinical devices supplied by three industrial partners. (2) Methods: Regarding the SNR improvement, advanced feature settings were proposed and verified based on free-field measurements made with an acoustic mannikin fitted with the different hearing aids. Regarding the gain prescription, a clinically feasible fitting tool and procedure based on real-ear gain adjustments were developed. (3) Results: Analyses of the collected real-ear gain and SNR improvement data confirmed the feasibility of the clinical implementation. Differences between the auditory profile-based fitting strategy and a current \u2018best practice\u2019 procedure based on the NAL- NL2 fitting rule were verified and are discussed in terms of limitations and future perspectives. (4) Conclusion: Based on a joint effort from academic and industrial partners, the BEAR fitting rationale was transferred to commercially available hearing aids.<\/div>

Close<\/a><\/p><\/div>

Narayanan, Sreeram Kaithali; Rye, Palle; Piechowiak, Tobias; Ravn, Gert; Wolff, Anne; Houm\u00f8ller, Sabina Storbjerg; Schmidt, Jesper Hvass; Hammersh\u00f8i, Dorte<\/p>

Can real-ear insertion gain deviations from generic fitting prescriptions predict self-reported outcomes?<\/a> Journal Article<\/span> <\/p>

The International Journal of Audiology, <\/span>62 <\/span>(5), <\/span>pp. 433-441, <\/span>2022<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{TIJA_SKN_J1,
\r\ntitle = {Can real-ear insertion gain deviations from generic fitting prescriptions predict self-reported outcomes?},
\r\nauthor = {Sreeram Kaithali Narayanan and Palle Rye and Tobias Piechowiak and Gert Ravn and Anne Wolff and Sabina Storbjerg Houm\u00f8ller and Jesper Hvass Schmidt and Dorte Hammersh\u00f8i},
\r\nurl = {https:\/\/doi.org\/10.1080\/14992027.2022.2053594},
\r\ndoi = {10.1080\/14992027.2022.2053594},
\r\nyear = {2022},
\r\ndate = {2022-04-07},
\r\njournal = {The International Journal of Audiology},
\r\nvolume = {62},
\r\nnumber = {5},
\r\npages = {433-441},
\r\nabstract = {Objective
\r\nThe aim of this study was to determine whether the differences in insertion gains from the first fit to generic prescriptions of hearing aids can predict the self-reported hearing aid (HA) outcomes for first-time and experienced HA users.
\r\n
\r\nDesign
\r\nThis was a prospective observational study.
\r\n
\r\nStudy Sample
\r\nThe study included 885 first-time and 330 experienced HA users with a valid real-ear measurement on both ears and answers to the abbreviated version of the Speech, Spatial, and Quality of Hearing (SSQ12) and the International Outcome Inventory for Hearing Aids (IOI-HA) questionnaires.
\r\n
\r\nResults
\r\nK-means clustering of gain differences between individual real-ear insertion gain to three generic gain prescriptions (NAL-NL2, NAL-RP, and one-third gain rules) was performed. The gain difference at higher frequencies generally differentiated the clusters. The experienced users in the cluster with fittings closest to NAL-NL2 and NAL-RP prescription were found to exhibit a higher IOI-HA Factor 1 score (representing the overall benefit of the hearing aid use). The gain differences to generic prescription did not affect other self-reported outcomes for first-time and experienced HA users.
\r\n
\r\nConclusion
\r\nThe experienced HA users with minimal gain deviations from generic prescriptions reported better self-perceived benefits than users with larger deviations. However, this was not apparent in first-time users.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/div>

Close<\/a><\/p><\/div>

Objective
\r\nThe aim of this study was to determine whether the differences in insertion gains from the first fit to generic prescriptions of hearing aids can predict the self-reported hearing aid (HA) outcomes for first-time and experienced HA users.
\r\n
\r\nDesign
\r\nThis was a prospective observational study.
\r\n
\r\nStudy Sample
\r\nThe study included 885 first-time and 330 experienced HA users with a valid real-ear measurement on both ears and answers to the abbreviated version of the Speech, Spatial, and Quality of Hearing (SSQ12) and the International Outcome Inventory for Hearing Aids (IOI-HA) questionnaires.
\r\n
\r\nResults
\r\nK-means clustering of gain differences between individual real-ear insertion gain to three generic gain prescriptions (NAL-NL2, NAL-RP, and one-third gain rules) was performed. The gain difference at higher frequencies generally differentiated the clusters. The experienced users in the cluster with fittings closest to NAL-NL2 and NAL-RP prescription were found to exhibit a higher IOI-HA Factor 1 score (representing the overall benefit of the hearing aid use). The gain differences to generic prescription did not affect other self-reported outcomes for first-time and experienced HA users.
\r\n
\r\nConclusion
\r\nThe experienced HA users with minimal gain deviations from generic prescriptions reported better self-perceived benefits than users with larger deviations. However, this was not apparent in first-time users.<\/div>

Close<\/a><\/p><\/div>

\r\n

2020<\/h3>\r\n <\/td>\r\n <\/tr>

Piechowiak, Tobias; Zapala, David<\/p>

Using BEAR data to obtain reduced versions of the SSQ-12 and IOI-HA-7 questionnaires Tobias Piechowiak<\/a> Inproceedings<\/span> <\/p>

Kressner, Abigail Anne; Regev, Jonathan; Christensen-Dalsgaard, Jakob; Tranebj\u00e6rg, Lisbeth; Santurette, S\u00e9bastien; Dau, Torsten (Ed.): Proceedings of the International Symposium on Auditory and Audiological Research, <\/span>pp. 237-264, <\/span>2020<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@inproceedings{ISAAR2019_TobiasP_pring\u00b4t,
\r\ntitle = {Using BEAR data to obtain reduced versions of the SSQ-12 and IOI-HA-7 questionnaires Tobias Piechowiak},
\r\nauthor = {Tobias Piechowiak and David Zapala},
\r\neditor = {Abigail Anne Kressner and Jonathan Regev and Jakob Christensen-Dalsgaard and Lisbeth Tranebj\u00e6rg and S\u00e9bastien Santurette and Torsten Dau },
\r\nurl = {https:\/\/proceedings.isaar.eu\/index.php\/isaarproc\/article\/view\/2019-29},
\r\nyear = {2020},
\r\ndate = {2020-05-01},
\r\nbooktitle = {Proceedings of the International Symposium on Auditory and Audiological Research},
\r\nvolume = {7},
\r\npages = {237-264},
\r\nabstract = {The Speech, Spatial and Qualities of Hearing scale (SSQ-12) and the International Outcome Inventory for Hearing Aids (IOI-HA-7) are questionnaires containing 12 and 7 items, respectively. They are designed to subjectively assess hearing ability and are complementary to behavioral measures. Both questionnaires have been applied across a range of clinical and clinical research-related contexts, for example for assessing outcomes of e.g., cochlear implants and hearing aids. However, due to time constraints neither of the questionnaires seem to be an inherent part of standard clinical quality control. The Better Hearing Rehabilitation (BEAR) database contains SSQ- 12 and IOI-HA-7 scores of around 1600 subjects. Applying an Exploratory Factor Analysis (EFA) on the data from the 2nd visit allowed us to reduce the SSQ-12 to 5 questions and the IOI-HA to 3 remaining questions. The SSQ-5 explains 79% of the variance in the SSQ-12 data while the IOI-HA-3 accounts for 70% of the variance in the original IOI-HA-7. These new versions have the potential to be used more efficiently by shortening time and focusing on the items that are most effective to reflect individual benefit. Furthermore, the analysis seems to confirm the validity of such a reduction from similar findings in the literature that were done on different datasets.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {inproceedings}
\r\n}
\r\n<\/div>

Close<\/a><\/p><\/div>

The Speech, Spatial and Qualities of Hearing scale (SSQ-12) and the International Outcome Inventory for Hearing Aids (IOI-HA-7) are questionnaires containing 12 and 7 items, respectively. They are designed to subjectively assess hearing ability and are complementary to behavioral measures. Both questionnaires have been applied across a range of clinical and clinical research-related contexts, for example for assessing outcomes of e.g., cochlear implants and hearing aids. However, due to time constraints neither of the questionnaires seem to be an inherent part of standard clinical quality control. The Better Hearing Rehabilitation (BEAR) database contains SSQ- 12 and IOI-HA-7 scores of around 1600 subjects. Applying an Exploratory Factor Analysis (EFA) on the data from the 2nd visit allowed us to reduce the SSQ-12 to 5 questions and the IOI-HA to 3 remaining questions. The SSQ-5 explains 79% of the variance in the SSQ-12 data while the IOI-HA-3 accounts for 70% of the variance in the original IOI-HA-7. These new versions have the potential to be used more efficiently by shortening time and focusing on the items that are most effective to reflect individual benefit. Furthermore, the analysis seems to confirm the validity of such a reduction from similar findings in the literature that were done on different datasets.<\/div>

Close<\/a><\/p><\/div>

Narayanan, Sreeram Kaithali; Piechowiak, Tobias; Wolff, Anne; Houm\u00f8ller, Sabina Storbjerg; Narne, Vijaya K; Loquet, G\u00e9rard; Hougaard, Dan Dupont; Gaihede, Michael; Schmidt, Jesper Hvass; Hammersh\u00f8i, Dorte<\/p>

Speech related hearing aid benefit index derived from standardized self-reported questionnaire data<\/a> Inproceedings<\/span> <\/p>

Kressner, Abigail Anne; Regev, Jonathan; Christensen-Dalsgaard, Jakob; Tranebj\u00e6rg, Lisbeth; Santurette, S\u00e9bastien; Dau, Torsten (Ed.): Proceedings of the International Symposium on Auditory and Audiological Research, <\/span>2020<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@inproceedings{ISAAR2019_sreeram_print,
\r\ntitle = {Speech related hearing aid benefit index derived from standardized self-reported questionnaire data},
\r\nauthor = {Sreeram Kaithali Narayanan and Tobias Piechowiak and Anne Wolff and Sabina Storbjerg Houm\u00f8ller and Vijaya K. Narne and G\u00e9rard Loquet and Dan Dupont Hougaard and Michael Gaihede and Jesper Hvass Schmidt and Dorte Hammersh\u00f8i},
\r\neditor = {Abigail Anne Kressner and Jonathan Regev and Jakob Christensen-Dalsgaard and Lisbeth Tranebj\u00e6rg and S\u00e9bastien Santurette and Torsten Dau },
\r\nurl = {https:\/\/proceedings.isaar.eu\/index.php\/isaarproc\/article\/view\/2019-45},
\r\nyear = {2020},
\r\ndate = {2020-04-14},
\r\nbooktitle = {Proceedings of the International Symposium on Auditory and Audiological Research},
\r\nvolume = {7},
\r\nabstract = {Speech understanding in noisy environments has been the most desired hearing-aid (HA) benefit sought by HA users. This paper examines the possibility of developing a speech-related HA benefit index from the speech- related questions in the self-reported questionnaire data. One question from Health-Related Quality of Life (HRQoL) instrument 15D and nine questions from the Speech, Spatial and Qualities of Hearing Scale (SSQ) having a direct implication to speech were selected for the analysis. After applying weights relevant to 15D, a delta of base-line (prior to HA fitting) and follow-up (two months after the initial fitting) responses to the selected questions were determined. A principal component analysis (PCA) was performed on the scaled and centered delta values. The resultant principal component scores were used to derive the composite index indicative of speech-related HA benefit.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {inproceedings}
\r\n}
\r\n<\/div>

Close<\/a><\/p><\/div>

\r\n

2018<\/h3>\r\n <\/td>\r\n <\/tr>

Sanchez-Lopez, Raul; Bianchi, Federica; Fereczkowski, Michal; Piechowiak, Tobias; Hau, Ole; Pedersen, Michael Syskind; Behrens, Thomas; Neher, Tobias; Dau, Torsten; Santurette, S\u00e9bastien<\/p>

Technical evaluation of hearing-aid fitting parameters for different auditory profiles<\/a> Conference<\/span> <\/p>

In Proceedings of Euronoise 2018, Crete, Greece, 27-31 May 2018, pp. 381-388, <\/span>2018<\/span>, ISSN: 2226-5147<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@conference{euronoise2018,
\r\ntitle = {Technical evaluation of hearing-aid fitting parameters for different auditory profiles},
\r\nauthor = {Raul Sanchez-Lopez and Federica Bianchi and Michal Fereczkowski and Tobias Piechowiak and Ole Hau and Michael Syskind Pedersen and Thomas Behrens and Tobias Neher and Torsten Dau and S\u00e9bastien Santurette},
\r\nurl = {http:\/\/www.euronoise2018.eu\/component\/contentbuilder\/details\/10\/83\/euronoise-2018-technical-evaluation-of-hearing-aid-fitting-parameters-for-different-auditory-profiles?Itemid=259},
\r\nissn = { 2226-5147},
\r\nyear = {2018},
\r\ndate = {2018-05-30},
\r\nbooktitle = {In Proceedings of Euronoise 2018, Crete, Greece, 27-31 May 2018, pp. 381-388},
\r\nabstract = {Hearing-aid users have reported an increased satisfaction since digital technology and advanced signal processing became available in hearing aids. However, many users still experience difficulties in noisy environments and in complex listening scenarios. Although numerous parameters can be adjusted to provide an individualized hearing solution, hearing-aid fitting currently consists of: 1) the gain prescription and adjustment based on the pure-tone audiogram, 2) the activation of advanced features on-demand, such as beamforming and noise reduction. In a previous study [1], a novel approach for auditory profiling was suggested, where the hearing deficits were characterized according to two types of distortion. This allowed the classification of listeners into four auditory profiles according to a high\/low degree of hearing distortions along the two dimensions. The aim of the present study was to evaluate different hearing-aid compensation strategies that may fit the needs of different auditory profiles via technical measures. A hearing-aid simulator, consisting of beamforming, noise reduction, and dynamic range compression, was used to test which parameter spaces and outcome measures may be of interest for a \u201cprofile-based hearing-aid fitting\u201d. The simulator consists of two dummy behind-the-ear hearing aids and off-line sound processing performed on a personal computer. Technical measures, such as signal-to-noise ratio (SNR) improvement, envelope degradation, and a metric of spectral distortions, were used to evaluate the effects of different signal processing strategies on the signal at the output of the simulator. Several parameter settings were evaluated using speech in the presence of various interferers at different SNRs. Here, the results of this technical evaluation are presented and discussed, with a view towards identifying the effective compensation strategies for different auditory profiles.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {conference}
\r\n}
\r\n<\/div>

Close<\/a><\/p><\/div>

Hearing-aid users have reported an increased satisfaction since digital technology and advanced signal processing became available in hearing aids. However, many users still experience difficulties in noisy environments and in complex listening scenarios. Although numerous parameters can be adjusted to provide an individualized hearing solution, hearing-aid fitting currently consists of: 1) the gain prescription and adjustment based on the pure-tone audiogram, 2) the activation of advanced features on-demand, such as beamforming and noise reduction. In a previous study [1], a novel approach for auditory profiling was suggested, where the hearing deficits were characterized according to two types of distortion. This allowed the classification of listeners into four auditory profiles according to a high\/low degree of hearing distortions along the two dimensions. The aim of the present study was to evaluate different hearing-aid compensation strategies that may fit the needs of different auditory profiles via technical measures. A hearing-aid simulator, consisting of beamforming, noise reduction, and dynamic range compression, was used to test which parameter spaces and outcome measures may be of interest for a \u201cprofile-based hearing-aid fitting\u201d. The simulator consists of two dummy behind-the-ear hearing aids and off-line sound processing performed on a personal computer. Technical measures, such as signal-to-noise ratio (SNR) improvement, envelope degradation, and a metric of spectral distortions, were used to evaluate the effects of different signal processing strategies on the signal at the output of the simulator. Several parameter settings were evaluated using speech in the presence of various interferers at different SNRs. Here, the results of this technical evaluation are presented and discussed, with a view towards identifying the effective compensation strategies for different auditory profiles.<\/div>

Close<\/a><\/p><\/div>