acoustic, atopic dermatitis, itch, piezoelectric element, scratch sound, visual analog scale.

Transcription

1 doi: / Journal of Dermatology 2014; 41: ORIGINAL ARTICLE Novel acoustic evaluation system for scratching behavior in itching dermatitis: Rapid and accurate analysis for nocturnal scratching of atopic dermatitis patients Yuichi NORO, 1 Youichi OMOTO, 2 Koji UMEDA, 2,3 Futa TANAKA, 1 Yousuke SHIRATSUKA, 1 Tomomi YAMADA, 4 Kenichi ISODA, 2 Kimiko MATSUBARA, 2 Keiichi YAMANAKA, 2 Esteban C. GABAZZA, 5 Masakatsu NISHIKAWA, 6 Hitoshi MIZUTANI 2 1 Department of Physics Engineering, Graduate School of Engineering, Departments of 2 Dermatology, 5 Immunology, Graduate School of Medicine, Mie University, 3 KSK Laboratory Incorporated, 4 Department of Biostatistics, Clinical Research Support Center, and 6 Clinical Trial Support Center, Mie University Hospital, Tsu, Japan ABSTRACT Quantitative analysis of itching in patients with itching dermatitis including atopic dermatitis (AD) is indispensable for the evaluation of disease activity and response to therapy. However, the objective evaluation system for itching is limited. We have developed a new objective and quantitative scratching behavior detection system using a wristwatch-type sound detector. The scratch sound detected on the wrist is recorded on a personal computer through a filtering, squaring and smoothing process by specific hardware. Subsequently, the data is automatically processed and judged for the scratching movement using specific software based on the periodicity and energy of the signal. Twenty-four measurements for healthy volunteers and those with AD by this system were evaluated by comparison with a simultaneously recorded video analysis system. The ratio of scratching time in sleeping time evaluated by these two systems was almost identical. The healthy subjects scratched their skin approximately 2 min during 6 h of sleeping time, while the mean scratching time of AD subjects was 24 min in their sleeping time. In contrast to the time-consuming video analysis system, this system takes only several minutes for evaluation of an overnight record. This scratch sound detection system is expected to serve as a new objective evaluation tool for itching dermatitis, namely, AD, and development of anti-itch therapies for dermatitis. Key words: acoustic, atopic dermatitis, itch, piezoelectric element, scratch sound, visual analog scale. INTRODUCTION Quantitative analysis of itching in patients with severe dermatitis including atopic dermatitis (AD) is indispensable for evaluation of disease activity and response to therapy. However, the objective evaluation system for itching is very limited. At present, itch in patients has been evaluated with a subjective quantitative system: a visual analog scale (VAS). 1 3 Because itch is described as an unpleasant sensation that elicits desire to scratch, 4 itch induces scratching behavior of the skin in AD patients, 5,6 and the scratching frequency of the skin closely relates to severity of the patient s itch 5 as well as some AD animal models. 7,8 The methods for quantitative evaluation for the scratching activity are counting the scratching movements by video or infrared video observation 5,6,9 or portable accelerometer. 10 Video observation is problematic in terms of the privacy of subjects and the burden placed on the observer. The portable accelerometer is convenient and suitable for detecting large movements of the arms, 10 but is not ideal for fine scratching movements limited to the fingers. For animal scratching detection, we have already proposed a new evaluation system for mouse scratching behavior without video observation. 8 This animal evaluation system clearly detects the mouse-scratching behavior by recording the air-conducted skin scratching sounds with the limbs. To apply this technology in humans, we developed a novel wristwatch type sound detection system (Fig. 1a). This detects exclusively the body-conducted scratching sounds, and we designed a sensor to record and evaluate the human scratching behavior. Here, we report a new sound-based scratching evaluation system, and compare it with a video-based analysis system in AD patients and normal subjects to measure its accuracy and time efficiency. Correspondence: Hitoshi Mizutani, M.D., Ph.D., Department of Dermatology, Mie University, Graduate School of Medicine, Edobashi, Tsu, Mie , Japan. h-mizuta@clin.medic.mie-u.ac.jp Received 8 November 2013; accepted 11 December Japanese Dermatological Association 233

2 Y. Noro et al. (a) (b) (c) Figure 1. (a) A sensor unit worn on the wrist for measurement fits well to the skin of the back of the wrist. Two wristwatch type sensor units are connected to a recording and processing unit box. (b) Illustrated figure of the cross-section view of the sensor unit. To prevent noise from the outside, the piezoelectric element is sealed in a concave aluminum cap (1 mm thick) with polyurethane gel and silicone sealant. (c) Schematic figure of the processing of the recorded sound in the processing box and output as data. ADC, analog digital converter; BPF, band-pass filter; HDD, high definition display; LPF, low-pass filter; PC, personal computer; TC, time constants. METHODS Body-conducted sound sensor The sensor unit has a wristwatch shape that adapts well to the wrist in addition to a wristwatch adhering to the skin of the dorsal portion of the forearm (Fig. 1a). The key device embedded in this unit is the thin piezoelectric element. The smallsized preamplifier integrated circuit (IC) chip (40-dB gain) is directly mounted on the back of the piezoelectric element. The IC chip was selected as the highest gain (40 db) amplifier available small-size IC. The fingertips and nails make specific sounds and imperceptible vibrations when scratching the body surface. This detection system clearly detects imperceptible vibration from fingertips at the wrists with a high sensitivity. To prevent invasion of the electrical and mechanical noise from outside the measuring surface, the piezoelectric element is sealed in a concave aluminum cap (1-mm thick) with polyurethane gel and silicone sealant (Fig. 1b). In addition, the piezoelectric element adheres to the skin surface with the viscous polyurethane gel. Therefore, the body-conducted sound energy is efficiently transmitted to the piezoelectric element. The analysis program detects scratching behavior based on the acquired sound signal information. Preprocessing hardware The signal from the body-conducted sound sensor is transferred and preprocessed in the interface box (Fig. 1c). The signal is passed through a band-pass filter (BPF) that has a pass band of Hz (Fig. 2a). The pass band of filtering was decided based on the difference of spectra between typical scratching sound and background noise. The BPF output is squared to obtain the energy-based signal. This signal is used for identification of the scratching time periods. Subsequently, the squared signal is divided and passed through two low-pass filters with different time constants each: 50 and 100 msec. This combination of time constants was decided by preliminary experiments to realize high detection accuracy. The difference between these two signals is calculated. The preprocessed signal shows simplified waves of energy (Fig. 2b). Finally, the signal is sampled with an analog digital converter (10-bit) at 100 Hz. The sampling rate was selected to avoid aliasing noise. Analysis software Analysis software. The analysis software truncates the sample signal into the fixed-length frame (5.12 s) and calculates autocorrelation of each frame in order to measure periodicity. The Japanese Dermatological Association

3 Evaluation of itch by scratch sound (a) exceeding a threshold value as scratching. Thus, non-specific sound and noises are eliminated effectively. (b) (c) Figure 2. (a) The simplified output signals from the band-pass filter. Data of the scratching sound shows a regular cyclic pattern, however, the noise of rolling over shows an irregular and non-cyclic pattern of short duration. (b) The preprocessed signal of scratching shows a simple wave of energy after processing of two low-pass filters. These waves are indicated for further analysis. (c) The autocorrelation values depicted in grayscale. The periodic pattern (stable stripes) is observed in the exact scratching movements. In contrast, the periodicity is not observed in sounds of the body rolling over and/or non-specific movements of the hands and fingers. calculation is repeated whenever the analysis frame is shifted by 0.32 s. The autocorrelations of each frame are integrated (Fig. 2c). The autocorrelation values are depicted in a gray scale. The periodic pattern (stable stripes) is observed in the exact scratching movements. In contrast, the periodicity is not observed in sounds of the body rolling over and non-specific movements of the hands and fingers. Thus, this analysis system enabled differentiation of the scratching behavior from non-specific movements or noises based on the periodicity and energy of the signal. Energy distinction. Scratching generates a sound by rubbing the skin with nails and fingers. To define scratching, three independent investigators evaluated the video-based scratching movements of the hands and fingers. Three investigators judged a movement that lasts more than 3 s as scratching. Then, this analysis system was programmed to select the successive frames, where the sound energy lasts more than 3 s Periodicity distinction. s max is defined as the delay time s when the autocorrelation / xx (s) is maximum in each frame. The scratching motion is distinguished based on the continuity of s max. It is assumed that s max is in the range of s when scratching. If the time length that s max is stable within fluctuating range 0.05 s is beyond 50% of the candidate frame s length, the program judges the presence of scratching movements and records their duration. The data analysis is automated using specific programs described above. Surprisingly, it takes only several minutes for processing the overnight data recorded in a personal computer to obtain the final scratching ratio. However, it took half a day to analyze the data simultaneously recorded by the video counting system. Video-record-based scratching count Movements of the hands and fingers were simultaneously captured using a video camera (DCR-TVR33; Sony, Tokyo, Japan) in the night-shot mode with light-emitting diode (LED) infrared illuminations (940-nm IR-LED, 1.5 W), and the data was recorded with a high definition display video camera (GZ-MG555-S; JVC Kenwood, Yokohama, Japan). According to the acoustic evaluation system, the scratching movements for 3 s and more were counted as scratching. The scratching time was counted from touching of fingers on the skin to the end of scratching. Verification experiments Subjects. This measurement was performed in 27 independent periods with the cooperation of four volunteers with AD 11 and eight healthy volunteers. The disease activities of AD subjects varied on the each measurement. The present study adhered to the tenets of the Declaration of Helsinki, and was approved by the institutional review board of Mie University Graduate School of Medicine (no. 2080). All participants provided written informed consent. Measurement of scratching. All the subjects wore the watchtype sensor units (Fig. 1a) during the night. The scratching sound in bed was recorded for approximately 6 h in a silent, air-conditioned room. The subjects were able to move freely and scratched their skin unconsciously. To verify the sound analysis program, the behavior of the subjects was recorded with a night-vision video camera simultaneously. Accuracy was verified comparing the results of our new system and that of the conventional video observation results. RESULTS Analysis and verification of scratching Scratching rate. The ratio of the scratching duration to the total sleeping time is described as scratching rate. The verti Japanese Dermatological Association 235

4 Y. Noro et al. cal axis is the rate obtained by the video observation, and the horizontal axis is the rate detected by the present scratch sound detection system (Fig. 3). The data aligned well, with a coefficient of determination as high as Difference between the scratching rate by video observation and by acoustic detection in the vertical axis (Fig. 4) was stable through low to high scratching count conditions (horizontal axis). Sleeping time. The mean sleeping time of normal subjects was 337 min and the mean sleeping time of AD patients was 326 min. There was no significant difference between the average sleeping time of AD patients and normal control. Scratching rate and scratching duration. Scratching rate of the normal subjects was approximately % (standard deviation) and the mean real scratching duration was approximately 2 min ( min). Surprisingly, the mean scratching rate of AD patients was %, which is significantly higher than that of normal subjects (Fig. 5). Thus, the mean real scratching duration was min, which is approximately 10-times higher than that of healthy control subjects. No specific complaints of sleeplessness, inconvenience or side-effects by wearing this device was reported from all tested subjects. Figure 4. Difference between the scratching rate by video observation and by acoustic detection in the vertical axis was stable through low to high scratching counts conditions (horizontal axis). DISCUSSION Figure 5. Nocturnal scratching rate between atopic dermatitis (AD) and control groups. The scratching duration of AD is more than 10-times longer than that of normal subjects. Figure 3. Comparative analysis of the nocturnal scratching rate between acoustic and visual counting system. The scratching rate measured by both systems clearly correlated from low to high scratching rate in a regression analysis. Itch (pruritus) is a subjective symptom that evokes an unpleasant sensation and scratching behavior of the skin. 4 Itch is a major symptom of acute and chronic dermatitis, especially AD. Itch compromises the host s quality life and exacerbates disease activities of AD with induction of inflammation and deterioration of the skin barrier functions by scratching. Therefore, measurement of itch has importance for evaluation of disease activities as well as therapeutic outcome. Unfortunately, itch is a subjective symptom, objective quantitative measurement of itch is very difficult, and no ideal system for has been introduced now. Therefore, a VAS has been widely used for evaluation of itch in AD to switch the subjective symptom to countable scale data. 1 3 However, there are still limitations in the objectivity and reproducibility of VAS measurements Japanese Dermatological Association

5 Evaluation of itch by scratch sound Conventional video or infrared-video observations have been used for evaluation of the movement of the hands and fingers, because of clear detection of scratching movement. 5,6 However, video-based counting has limitations in detection of blind positioned hands. It is also problematic in terms of privacy and is time-consuming for evaluation of the overnight recorded movies even when using a specific rapid observation system. 12 Therefore, the results are not available immediately after examination by video-based counting systems. A portable accelerometer designed for wrist wearing has been used for evaluation for sleep, 13,14 body movements 15 and physical activities. 16 It is also indicated for detection of hand movements in AD patients. 10 Originally, these devices were designed for observation of body activities. An accelerometer detects large movements of the wrist and counts strokes of the arms using specifically prepared software. However, its effects in detection of small movements including scratching with the fingers without moving the arms are still unclear. A specific program for sensitive detection of fine movements or placement of the sensors on the fingers may be required for evaluation of fine finger movements. Accuracy and rapid processing are attractive features of this acoustic counting system. As we expected, the difference between the scratching counts by video and acoustic methods are very limited. The coefficient of determination is as high as 0.98, which is higher than that of the reported wristwatch type accelerometer. 10 The difference between video and acoustic methods in the most different case was under 2%. This difference did not vary with the increase in scratch counts (Fig. 4). In contrast, the evaluation time between the acoustic counting and video counts was very different. The processing time of the acoustic system was within several minutes, but the simultaneously recorded video counting required several hours. The count was close to the real-time counting system. Patients scratch their skin using their fingernails, and make scratching sounds with the fingertips. Patients and persons sitting nearby may hear the scratching sounds. We have already reported an evaluation system for an AD mouse model detecting their scratching air-conducted sounds without video observation. 8 However, detection of the air-conducted scratching sound was indicated for the mouse-derived sounds in a closed measuring box, but not for the human-derived sounds in the open air. The air-conducted noises including voice, clothes and air conditioners disturb accurate counting of the scratching sounds. Therefore, we developed a novel detection system for the sound conducted from fingertips to wrists through the finger and wrist bones. Our system selectively detects the specific bone-conducted sounds on the wrist, eliminating the surrounding noises. Mental stress and emotional factors affect scratching behavior in humans, and we evaluated the nocturnal scratching behavior in AD patients and normal subjects in the present study. Interestingly, the scratching behavior for itch has a specific feature: cyclic nature. As reported previously, the scratching behavior in mouse AD models 8 has cyclicity. In scratching movement in human AD patients, a video analysis revealed rhythmic, monotonous and cyclic nature in movement of a few seconds in duration. 9 Cyclicity of the scratching in AD patients is very clear compared with irregularities in non-specific movements of the hands (Fig. 2). There is risk of intrusion of noise and non-specific movements. The scratching movement in AD patients is clear and detectable under blankets, 9 and the presence of blankets and clothes did not affect to the present recorded scratch sound data (not shown). In a preliminary study, the noise from outer circumstances that was detectable without the cap and sealing systems was successfully omitted by the hard shell sealing (data not shown). Additionally, duration of scratching has importance. Video-based observation by three investigators declared that to accurately detect a scratching movement they must last more than 3 s. In combination with cyclicity, the noise and non-specific movement of the hands are successfully eliminated by this system. Thus, the clear specific scratching sound waves in human scratching behavior were measured in this study. Surprisingly, AD patients scratched their skin for more than 20 min in bed, which was approximately 7% of their sleeping time. This implicates deterioration of quality of life in AD patients, and the importance of itch control in AD therapies. The results obtained in the present study prove the accuracy and convenience of this wristwatch type acoustic scratch detection system. In addition, the very rapid processing time, several minutes for 6 h recorded data, is very attractive. A further largescale trial is required for evaluation of the present system. This acoustic scratch analysis system is expected to serve as a potent tool for evaluation of the disease activities of AD as well as outcome of therapies for the itching skin diseases. ACKNOWLEDGMENTS: Y. N., H. M., K. I. and K. U. received grants from Mie Prefecture for the development of medical instruments based on collaboration between medical and engineering institutions. Y. N. received a JST project to develop innovative seeds (2008). Y. O. (no ), K. Y. (no ) and H. M. (no ) received grants for scientific research from the Ministry of Education, Culture, Sports, Science and Technology, Japan. The other authors did not receive any financial support. CONFLICT OF INTEREST: Y. N. and H. M. have the basic patent ( ) for the sound-based detection system of the movement for animals and human. H. M., Y. N., K. I. and K. U. have a financial interest in KSK Laboratories Incorporated, a company that may have commercial interest in the results of this research and technology. REFERENCES 1 Furue M, Ebata T, Ikoma A et al. Verbalizing extremes of the visual analogue scale for pruritus: a consensus statement. Acta Derm Venereol 2013; 93: Severity scoring of atopic dermatitis: the SCORAD index. consensus report of the European task force on atopic dermatitis. Dermatology 1993;186: Phan NQ, Blome C, Fritz F et al. Assessment of pruritus intensity: prospective study on validity and reliability of the visual analogue scale, numerical rating scale and verbal rating scale in 471 patients with chronic pruritus. Acta Derm Venereol 2012; 92: Japanese Dermatological Association 237

6 Y. Noro et al. 4 Ikoma A, Steinhoff M, Stander S, Yosipovitch G, Schmelz M. The neurobiology of itch. Nat Rev Neurosci 2006; 7: Ebata T, Aizawa H, Kamide R. An infrared video camera system to observe nocturnal scratching in atopic dermatitis patients. J Dermatol 1996; 23: Endo K, Sano H, Fukuzumi T, Adachi J, Aoki T. Objective scratch monitor evaluation of the effect of an antihistamine on nocturnal scratching in atopic dermatitis. J Dermatol Sci 1999; 22: Tanizaki H, Kambe N, Nakamura Y, Tanaka A, Matsuda H, Miyachi Y. Oral administration of bepotastine besilate suppressed scratching behavior of atopic dermatitis model NC/Nga mice. Int Arch Allergy Immunol 2008; 145: Umeda K, Noro Y, Murakami T et al. A novel acoustic evaluation system of scratching in mouse dermatitis: rapid and specific detection of invisibly rapid scratch in an atopic dermatitis model mouse. Life Sci 2006; 79: Ebata T, Aizawa H, Kamide R, Niimura M. The characteristics of nocturnal scratching in adults with atopic dermatitis. Br J Dermatol 1999; 141: Ebata T, Iwasaki S, Kamide R, Niimura M. Use of a wrist activity monitor for the measurement of nocturnal scratching in patients with atopic dermatitis. Br J Dermatol 2001; 144: Katayama I, Kohno Y, Akiyama K et al. Japanese guideline for atopic dermatitis. Allergol Int 2011; 60: Izumi H, Ebata T, Sato T, Aizawa H, Kamide R, Niimura M. A simplified method for the measurement of nocturnal scratching with an infrared video camera. (In Japanese). Skin Res 1997; 39: Tremaine R, Dorrian J, Paterson J et al. Actigraph estimates of the sleep of Australian midwives: the impact of shift work. Biol Res Nurs 2013; 15: Meltzer LJ, Westin AM. A comparison of actigraphy scoring rules used in pediatric research. Sleep Med 2011; 12: Tryon WW. Issues of validity in actigraphic sleep assessment. Sleep 2004; 27: Vanhelst J, Beghin L, Turck D, Gottrand F. New validated thresholds for various intensities of physical activity in adolescents using the Actigraph accelerometer. Int J Rehabil Res 2011; 34: Japanese Dermatological Association