Performance Outcomes of Nucleus® 6 SmartSound® iQ Technology with the First Cochlear Implant Scene Classifier Introduction Almost all listening environments contain some level of background noise, originating from a variety of sources with a range of spectral characteristics. Stationary or diffuse noise tends to have relatively low amplitude modulations which typically fall outside the speech spectrum (Plomp, 1983; Rosen, 1992) such as noise from traffic or room ventilation systems. In contrast, competing speech noise often has acoustic properties very similar to those of the target speech, producing a more challenging listening situation (Festen & Plomp, 1990). Background noise can also be generated from environmental sources such as wind, which has a typically intense low-frequency spectrum that is particularly annoying to individuals using hearing devices. Given the many different existing noise types, and that combinations of these may be unique to every cochlear implant (CI) recipient’s listening environments, no single input processing or sound coding technology is sufficient to provide maximum performance benefits and comfort. A multifaceted approach involving a range of technologies specifically designed to target different noise situations is required. Nucleus SmartSound and SmartSound 2 technology CochlearTM has actively researched solutions to overcome the challenges of listening in noise, culminating in the introduction of Nucleus® SmartSound® technology in 2005. SmartSound encompassed a variety of input processing technologies including Automatic Sensitivity Control (ASC), channel-specific Adaptive Dynamic Range Optimisation (ADRO®), together with a range of microphone directionality (Patrick et al., 2006). ASC is a slow acting algorithm designed to automatically reduce the level of noise in a noisy environment (Seligman & Whitford, 1995: Patrick et al., 2006), while ADRO is a pre-processing technology that continuously adjusts the gain in each channel to place the signal optimally within the electrical hearing dynamic range (Blamey, 2005). The use of directional microphones has proven to be very effective in reducing the interference of noise in hearing aid recipients (Killion, 2004; Bentler, 2005), and were first introduced into Nucleus sound processors in the mid 1980’s (Blamey et al., 1987). SmartSound technologies included the first dual microphone adaptive beamforming algorithm called Beam®, shown to deliver significant hearing benefit in competing (multi-talker babble) noise (Spriet et al., 2007; Chung & Zeng, 2009; Hersbach et al., 2012; Wolfe et al., 2012). The release of SmartSound 2 in 2009 delivered further noise management advances with the Nucleus 5 CP810 Sound Processor and CR110 Remote Assistant. SmartSound 2 offered the flexibility to combine different input processing options for customised Everyday, Noise, Focus and Music programs. The use of calibrated, dual, omni-directional microphones provided an expanded suite of directionality including the fixed super-directionality of zoom processing, ideal for attenuating constant distracting noise sources. Studies have demonstrated the benefits of having a range of microphone directionality patterns available, benefitting users across a range of listening environments (Preves et al, 1999; Powers & Hamacher, 2002; Wolfe et al., 2012). SmartSound iQ with SCAN The recent release of the Nucleus 6 (CP900 series) sound processor delivers the newest generation of SmartSound technology called SmartSound iQ (SSiQ), with an industry first automatic scene classifier termed SCAN. SmartSound iQ delivers several new options for improved hearing performance and listening comfort in noise, including an advanced background noise reduction algorithm (SNR-NR) and a wind noise detection and reduction algorithm (WNR). SmartSound iQ noise reduction (SNR-NR) is designed specifically for CI sound processor requirements to attenuate constant background noises irrespective of their direction. This technology detects the background noise level in each frequency channel, estimates the signal-to-noise ratio (SNR) in each channel ­— for each time sample — and attenuates those channels having low SNRs which are indicative of background noise. SNR-NR acts instantaneously to reduce background noise levels while retaining speech and other important signals (Hersbach et al., 2012; Mauger et al., 2012). Annoyance from wind noise is a common complaint from hearing aid and cochlear implant recipients. Wind noise is even more problematic with directional microphone systems due to greater low frequency noise from wind (Chung et al., 2009; Chung & McKibben, 2011) and distortions to microphone directionality (Chung, 2012). With SmartSound iQ, when wind noise is detected, the microphone directionality is optimised for use in wind. Specifically designed multichannel compressors are then activated to reduce the low frequency wind noise while retaining other sounds. A pilot study evaluating wind noise reduction in the Nucleus cochlear implant sound processors indicated positive speech understanding and listening quality results (Goorevich et al., 2012b). Until now, SmartSound technologies were typically provided to recipients via a number of different listening programs, manually switched using a remote assistant or via the processor buttons. In this format, a number of factors may prevent many cochlear implant recipients from achieving their best hearing performance at all times including, dexterity issues, the need to manually change programs, uncertainty as to when to change programs, and the possibility of selecting the ‘wrong’ program in specific listening environments. To address this, the Nucleus 6 sound processor offers a scene classifier (SCAN), providing automatic detection of a user’s listening environment, and automatic selection of appropriate settings without the need for multiple processor programs or manual program changes. Many state-of-the-art hearing aids currently use ’environmental classification‘, whereby the audio input signal is categorised into one or more ’scenes‘ to determine appropriate characteristics for automatic program selection (Allegro et al., 2001; Büchler et al., 2005). Recent pilot research has indicated that this type of automatic scene classification and program selection can benefit cochlear implant recipients as well (Case et al., 2011; Goorevich et al., 2012a). 2 | Nucleus 6 SmartSound iQ | December 2013 The SCAN program analyses microphone input signals and classifies the sound environment into one of six scenes (Speech in Noise, Speech, Noise, Wind, Quiet and Music). For each scene, SCAN selects the most appropriate microphone directionality pattern (standard, fixed or adaptive) and activates the appropriate scene technology based on the determined environment. Changes in settings are transitioned smoothly to avoid any abrupt or disruptive listening percept for the recipient. In addition to controlling the input processing technologies for each scene, SCAN also stores the scene classification on the Nucleus 6 sound processor. Datalogging of scene information can be reviewed off-line by a clinician for troubleshooting, device counselling and/or program optimisation, offering objective insights. This paper presents the performance outcomes of adults fitted with the Cochlear Nucleus 6 sound processor using SmartSound iQ with SCAN. Materials and Methods Subjects Twenty-one Australian adults, using a mix of Nucleus CI500 Series and CI24RE cochlear implants, participated in the study. The mean age for this group was 67.8 years, with a range of 49 to 90 years. Average length of cochlear implant use was 5.6 years, ranging from one to 15 years. Study design The study used a repeated-measures, single-subject design, in which each subject served as his or her own control. Subjects were evaluated using their existing Nucleus 5 (CP810) sound processor and the new Nucleus 6 (CP900) sound processor with SmartSound iQ. Sentence perception in noise with different listening programs was compared for each subject across five test sessions, and the order in which the programs were tested was counter-balanced to control for order effects. Prior to testing, all recipients had a minimum of two weeks use of the Nucleus 6 sound processor to acclimatise to the default program. Listening programs Study participants used their preferred listening program in noise with their Nucleus 5 sound processor, with 57% of subjects choosing the Noise program (with zoom processing) and 24% choosing the Focus program (with Beam). The remaining 19% used a variety of other listening programs with standard microphone directionality. Speech perception scores with their Nucleus 6 sound processor were obtained using a variety of programs with differing combinations of input processing options including the default automatic SCAN program. The programs tested are listed in Table 1. Nucleus 6 SmartSound iQ | December 2013 3 Table 1: A description of technologies used in sound processor programs. Tilde (~) denotes the technology as selected by the clinician/subject for listening in noise. Asterisk (*) denotes the use of a specific technology for a given program. Audibility Microphone Directionality System Program AGC ASC ADRO Standard zoom Beam Nucleus 5 Preferred * ~ ~ ~ ~ ~ Nucleus 6 No SmartSound Everyday * * * * SCAN * * * Noise Reduction SNR-NR * * automatic * Speech perception All testing in noise was conducted using the Australian sentence test in noise (AuSTIN), which is an adaptive SRT sentence test using either speech weighted noise (SWN) or 4-talker babble (4TB) as the noise source (Dawson et al., 2013). This test determines the signal-to-noise ratio (SNR) for 50% sentence intelligibility with each listening program. The target speech signal was presented at a fixed 65 dB SPL (RMS) level from a speaker positioned in front of the subject. Testing was conducted using both SWN and 4-talker babble noise which was increased or decreased based on the subjects’ response. Both noise types were tested in two different spatial configurations, S0N0 (signal at 0 degrees, noise at 0 degrees) and S0N3 (signal at 0 degrees, noise at 90, 180 and 270 degrees). All speech and noise configurations had the speaker locations at 1.2m from the listening position. Each test run comprised 20 sentences from which individual SRTs were calculated. Two SRTs for the same test condition were then averaged to determine each subject’s mean SRT score. Results were analysed using a repeated measures one-way analysis of variance (ANOVA) with post-hoc Newman-Keuls comparisons to determine the effect of program. 4 | Nucleus 6 SmartSound iQ | December 2013 Results 1. Significant directional microphone benefit shown in 4 talker babble Figure 1 shows the group mean SRTs at 65 dB SPL in spatially separated (S0N90,180,270) 4TB noise with the Nucleus 6 sound processor. A lower SRT (dB SNR) value indicates an improved speech perception outcome. The SCAN program automatically selected adaptive directionality (Beam) in this condition and achieved a group mean SRT of -3.9 dB which was significantly better than the ‘No SmartSound’ and ‘Everyday’ conditions with SRT’s of 0.0 and -0.4 dB, respectively, using standard microphone directionality (p<0.001). The average SRT benefit of SCAN over the ‘No SmartSound’ and ‘Everyday’ conditions was 3.9 and 3.5 dB, respectively. S N N 4TB | 65 dB SPL | N=21 N 0.0 NO SMARTSOUND -0.04 SMARTSOUND iQ WITH SCAN PROGRAM SMARTSOUND 2 EVERYDAY Results reinforce that adaptive microphone directionality such as Beam, is valuable for listening to speech in noise where the noise source is to the rear and sides of the recipient -0.37 SRT (dB) -1.0 -2.0 -3.0 -3.86 -4.0 -5.0 *** *** -6.0 STANDARD DIRECTIONALITY STANDARD DIRECTIONALITY ASC + ADRO ADAPTIVE (Beam) DIRECTIONALITY ASC + ADRO Figure 1: Shows the mean SRT scores presented in 4TB using the S0N3 speaker configuration. Error bars show standard error of the means. Asterisks show significant differences (***p<0.001). Nucleus 6 SmartSound iQ | December 2013 5 2. Noise reduction (SNR-NR) benefit in speech weighted noise Figure 2 shows the group mean SRTs at 65 dB SPL in SWN with speech and noise coincident (S0N0) using the Nucleus 6 sound processor. In this challenging listening condition where both speech and noise are delivered from a speaker in front of the listener, a lower SRT value indicates an improved speech perception outcome. The SCAN program using SNR-NR in this speech and noise condition resulted in a group mean SRT of -2.9 dB, significantly better (p<0.001) than the ‘No SmartSound’ and ‘Everyday’ SRTs of -0.58 and -1.3 dB. No significant difference in SRT was shown between the ‘No SmartSound’ and ‘Everyday’ conditions. The average SRT benefit offered by SCAN over the ‘No SmartSound’ and ‘Everyday’conditions was 2.3 and 1.6 dB, respectively. S+N SWN | 65 dB SPL | N=21 0.0 NO SMARTSOUND SMARTSOUND iQ WITH SCAN PROGRAM SMARTSOUND 2 EVERYDAY -0.58 SRT (dB) -1.0 -1.33 -2.0 -2.88 -3.0 -4.0 -5.0 *** *** -6.0 STANDARD DIRECTIONALITY STANDARD DIRECTIONALITY ASC + ADRO FIXED (zoom) DIRECTIONALITY ASC + ADRO Figure 2: Shows the mean SRT scores presented in SWN using the S0N0 speaker configuration. Error bars show standard error of the mean. Asterisks show significant differences (***p<0.001). 6 | Nucleus 6 SmartSound iQ | December 2013 The improvement shown is predominantly due to the SNR-NR algorithm rather than directional microphones since the speech and noise signals are co-located in this condition. These results suggest that existing recipients will gain significant performance benefits in noise by accessing new Smart Sound iQ noise reduction technology. 3. SCAN shows performance benefits for non-SmartSound recipients Figure 3 shows the mean SRTs at 65 dB SPL in both 4TB and SWN using the Nucleus 6 sound processor with a spatially separated (S0N90,180,270) speaker setup. As in previous figures the ‘No SmartSound’ condition represents recipients who use only standard microphone directionality with all other technologies disabled. A lower SRT value indicated an improved speech perception outcome. The SCAN program using microphone directionality and SNR-NR, resulted in a group mean SRT of -3.9 dB in 4TB and -7.6 dB in SWN, significantly better than the ‘No SmartSound’ condition which resulted in SRTs of 0.0 and -2.8 dB, respectively (p<0.001). S N N N 0.0 4TB NO SMARTSOUND | 65 dB SPL | N=21 SMARTSOUND iQ 0.0 SWN NO SMARTSOUND SMARTSOUND iQ -0.04 -1.0 SRT (dB) SRT (dB) -1.0 -2.0 -3.0 -2.0 -2.83 -3.0 -3.86 -4.0 -5.0 -4.0 -5.0 *** -6.0 -6.0 STANDARD DIRECTIONALITY ADAPTIVE (Beam) DIRECTIONALITY ASC + ADRO -7.0 -7.63 -8.0 STANDARD DIRECTIONALITY *** FIXED (zoom) DIRECTIONALITY ASC + ADRO Figure 3: Shows the mean SRT scores presented in 4TB and SWN using the S0N3 speaker configuration. Error bars show standard error of the mean. Asterisks show significant differences (***p<0.001). The improvement shown results from directional microphone algorithms (zoom and Beam) and SNR-NR. These results suggest that use of SmartSound iQ technologies offer substantial hearing performance benefits, and that recipients who do not currently access them due to clinical fitting practices, choice of sound processor, or personal preference will gain significant hearing benefits with the SCAN program. Nucleus 6 SmartSound iQ | December 2013 7 4. SCAN shows performance benefits for experienced SmartSound users Figure 4 shows the mean SRTs at 65 dB SPL in SWN (S0N0 and S0N90,180,270) using Nucleus 5 and Nucleus 6 sound processors. Recipients in this study are experienced SmartSound users, more than 80% of whom routinely switch to a directional SmartSound 2 program for listening in noise. For the S0N0 configuration, Nucleus 6 with SCAN resulted in a group mean SRT of -2.9 dB which was significantly better than the Nucleus 5 condition which resulted in a mean SRT of -1.2 dB (p<0.001). For the S0N90,180,270 condition, a mean SRT of -7.6 dB was obtained with Nucleus 6, which was significantly better than the -6.3 dB SRT obtained for the Nucleus 5 condition (p<0.001). S+N S SWN | 65 dB SPL | N=21 N N N SRT (dB) -1.0 0.0 NUCLEUS 5 NUCLEUS 6 -1.0 -1.23 -2.0 -2.88 -3.0 -4.0 SRT (dB) 0.0 NUCLEUS 6 NUCLEUS 5 -2.0 -3.0 -4.0 *** -5.0 -5.0 -6.0 -6.0 PREFERRED NOISE PROGRAM FIXED (zoom) DIRECTIONALITY ASC + ADRO -6.35 -7.0 -7.63 -8.0 *** PREFERRED NOISE FIXED (zoom) PROGRAM DIRECTIONALITY ASC + ADRO Figure 4: Shows the mean SRT scores presented in SWN using S0N0 and S0N3 speaker configuration. Error bars show standard error of the mean. Asterisks show significant differences (***p<0.001). Results suggest that even experienced users of a Nucleus 5 Sound Processor with SmartSound 2 are likely to gain improved speech understanding in noise (in addition to reduced inconvenience from manually switching sound processor settings) by upgrading to Nucleus 6 and accessing SNR-NR and the automated SCAN technology. 8 | Nucleus 6 SmartSound iQ | December 2013 Conclusion All recipients successfully upgraded to the Nucleus 6 system and preferred SCAN as their default listening program. SmartSound iQ and SCAN technologies produced significant benefits for listening in both steady-state and multi-talker babble noise when compared to ‘No SmartSound’ and ‘Everyday’ listening programs. The Nucleus 6 sound processor with SmartSound iQ provides significant performance improvements over a standard microphone configuration in spatially separated noise. The availability of a clinically relevent background noise reduction algorithm (SNR-NR) provides additional performance benefits for Nucleus 6 recipients, especially when tested in SWN. For recipients with a Nucleus 5 sound processor converting to a Nucleus 6 sound processor, these study findings demonstrate the new SmartSound iQ technology will provide hearing benefits. With the automatic scene classifier (SCAN) in the Nucleus 6 system enabled for routine use, optimal and consistent scene selection is automatically achieved in each sound environment. Comprehension improved significantly over levels achieved with the Nucleus 5 system. Cochlear continues to deliver performance benefits. The industry’s first scene classifier (SCAN) will enable existing and newly implanted recipients to easily and automatically enhance their comprehension and listening experience. Nucleus 6 SmartSound iQ | December 2013 9 NOTES 10 | Nucleus 6 SmartSound iQ | December 2013 References Allegro S, Büchler M, Launer S (2001). Automatic sound classification inspired by auditory scene analysis. In: Proc European Conf Sig Proc, (EURASIP). Hersbach AA, Arora K, Mauger SJ, Dawson PW (2012). Combining directional microphone and single-channel noise reduction algorithms: a clinical evaluation in difficult listening conditions with cochlear implant users. Ear and Hearing 33:13-23. Bentler RA (2005). The effectiveness of microphones and noise reduction schemes in digital hearing aids: a systematic review of the evidence. J Am Acad Audiol 16, 473-84. Killion, MC (2004). Myths about hearing in noise and directional microphones. Hearing Review, 11(2). Blamey PJ, Dowell RC, Clark GM, Seligman P (1987). Acoustic parameters measured by a formant estimating speech processor for a multiple-channel cochlear implant. J Acoust Soc Am 82(1), 38-47. Mauger SJ, Dawson PW, Hersbach AA (2012). Perceptually optimized gain function for cochlear implant signal-to-noise ratio based noise reduction. The Journal of the Acoustical Society of America 131:327-336. Blamey PJ (2005). Adaptive dynamic range optimization (ADRO): a digital amplification strategy for hearing aids and cochlear implants. Trends Amplif 9:77-98. Patrick JF, Busby PA, Gibson PJ (2006). The development of the Nucleus Freedom Cochlear implant system. Trends Amplif 10:175-200. Büchler M, Allegro S, Launer S (2005). Sound Classification in Hearing Aids Inspired by Auditory Scene Analysis. EURASIP Journal of Applied Signal Processing 18:2991-3002. Case S, Goorevich M, Gorrie J, Nesselroth Y, Plant K, Knight M (2011). Evaluation of an environmental classifier with adult cochlear implant recipients using the CP810 sound processor. In: CI2011. Chung K (2012). Wind noise in hearing aids: II. Effect of microphone directivity. Int J Audiol 51:29-42. Chung K, McKibben N (2011). Microphone directionality, pre-emphasis filter, and wind noise in cochlear implants. Journal of the American Academy of Audiology 22:586-600. Chung K, Mongeau L, McKibben N (2009). Wind noise in hearing aids with directional and omnidirectional microphones: polar characteristics of behind-the-ear hearing aids. The Journal of the Acoustical Society of America 125:2243-2259. Chung K, Zeng FG (2009). Using hearing aid adaptive directional microphones to enhance cochlear implant performance. Hearing Research 250:27-37. Dawson P, Hersbach AA, Swanson B (2013). An Adaptive Australian Sentence Test in Noise (AuSTIN). Ear and Hearing 23(5), 592-600 Festen JM, Plomp R (1990). Effects of fluctuating noise and interfering speech on the speech-reception threshold for impaired and normal hearing. J Acoust Soc Am. 88(4), 1725-36. Goorevich M, Case S, Gorrie J, Nesselroth Y, Plant K (2012a). Feasibility of an Environmental Classifier with Adult Cochlear Implant Recipients. 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Temporal information in speech: Acoustic, auditory and linguistic aspects, Philos Trans R Soc London, Ser. B 336, 367-373. Seligman, P, & Whitford, L, (1995). Adjustment of appropriate signal levels in the Spectra 22 and mini speech processors. The Annals of Otology, Rhinology & Laryngology. Supplement, 166, 172. Spriet A, van Deun L, Eftaxidias K, Laneau J, Moonen M, van Dijk B, van Wieringen A, Wouters J. (2007). Speech understanding in background noise with the two-microphone adaptive beamformer BEAM in the Nucleus Freedom cochlear implant system. Ear and Hearing 28(1), 6272. Wolfe J, Parkinson A, Schafer EC, Gilden J, Rehwinkel K, Mansanares J, Coughlan E, Wright J, Torres J, Gannaway S (2012). Benefit of a commercially available cochlear implant processor with dual-microphone beamforming: a multi-center study. Otology & Neurotology: official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology 33:553560. As the leading global expert in implantable hearing solutions, Cochlear is dedicated to bringing the gift of sound to people all over the world. For thirty years, Cochlear has pioneered this technology, helping hundreds of thousands of people reconnect to their families and friends. Along with the industry’s largest investment in research and development, we continue to partner with leading international researchers and hearing professionals, ensuring that we are at the forefront of hearing science. For our customers, that means access to our latest technologies throughout their lives, and the ongoing support they need. That is why seven out of ten people worldwide who choose a cochlear implant choose Cochlear as their hearing partner. Acknowledgements The authors would like to acknowledge the researchers, audiologists and recipients who contributed to the data and analysis reported in this paper. 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