Pengembangan Instrumentasi dan Analisis Sinyal EMG pada Otot Leher

Orang yang telah kehilangan laring (laryngectomee) atau mengalami kerusakan laring akan kehilangan fungsi bicara dan menyebabkan sulitnya berkomunikasi. Electrolarynx (EL) adalah perangkat genggam berdayakan baterai yang merupakan salah satu alternatif untuk membangkitkan suara dengan memberi getaran pada otot leher. EL adalah alternatif yang mudah digunakan dan sederhana, akan tetapi suara yang dihasilkan EL tidak natural (seperti robot), monoton, dan memiliki kualitas yang rendah sehingga dibutuhkan pengembangan lanjut untuk meningkatkan kualitas suara dan kenyamanan penggunaan. Penelitian sebelumnya telah menunjukkan adanya hubungan antara aktivitas otot leher dengan pembentukan suara. Oleh karenanya, sinyal elektromiografi (EMG) pada otot leher dianalisis terhadap intensinya untuk memulai/berhenti bicara dan hubungannya dengan nada suara yang dihasilkan. Pada penelitian ini, instrumentasi EMG minimum dirancang untuk memperoleh sinyal EMG pada otot leher. Instrumentasi EMG terdiri dari penguat instrumentasi, rangkaian filter, dan rangkaian adder. Sinyal EMG kemudian direkam dan dilakukan proses filtering, rectification, dan kalkulasi envelope sinyal sederhana dengan low pass filter Pole-Zero. Korelasi amplitudo envelope EMG dengan sinyal suara ketika berbicara dianalisis. Thresholding sinyal EMG dengan batas ambang ganda (onset/offset) diusulkan dalam mendeteksi sinyal wicara. Hasil penelitian ini menunjukkan bahwa perekaman sinyal EMG pada otot leher membutuhkan instrumentasi dengan penguatan yang jauh lebih besar. Nilai threshold untuk onset mampu mendeteksi sinyal wicara sebelum wicara terjadi dengan selang waktu sekitar 0.2 ms. Akan tetapi, offset threshold tidak mampu memberikan waktu akhir dari sinyal wicara dengan tepat, di mana deteksi wicara diakhir lebih cepat sekitar 0.12 ms dari seharusnya

Prediction of larynx function using multichannel surface EMG classification

Total laryngectomy (TL) affects critical functions such as swallowing, coughing and speaking. An artificial, bioengineered larynx (ABL), operated via myoelectric signals, may improve quality of life for TL patients. To evaluate the efficacy of using surface electromyography (sEMG) as a control signal to predict instances of swallowing, coughing and speaking, sEMG was recorded from submental, intercostal and diaphragm muscles. The cohort included TL and control participants. Swallowing, coughing, speaking and movement actions were recorded, and a range of classifiers were investigated for prediction of these actions. Our algorithm achieved F1-scores of 76.0 ± 4.4 % (swallows), 93.8 ± 2.8 % (coughs) and 70.5 ± 5.4 % (speech) for controls, and 67.7 ± 4.4 % (swallows), 71.0 ± 9.1 % (coughs) and 78.0 ± 3.8 % (speech) for TLs, using a random forest (RF) classifier. 75.1 ± 6.9 % of swallows were detected within 500 ms of onset in the controls, and 63.1 ± 6.1 % in TLs. sEMG can be used to predict critical larynx movements, although a viable ABL requires improvements. Results are particularly encouraging as they encompass a TL cohort. An ABL could alleviate many challenges faced by laryngectomees. This study represents a promising step toward realising such a device

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy

Inside the conductor's jacket : analysis, interpretation and musical synthesis of expressive gesture

Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.Includes bibliographical references (leaves 154-167).We present the design and implementation of the Conductor's Jacket, a unique wearable device that measures physiological and gestural signals, together with the Gesture Construction, a musical software system that interprets these signals and applies them expressively in a musical context. Sixteen sensors have been incorporated into the Conductor's Jacket in such a way as to not encumber or interfere with the gestures of a working orchestra conductor. The Conductor's Jacket system gathers up to sixteen data channels reliably at rates of 3 kHz per channel, and also provides mcal-time graphical feedback. Unlike many gesture-sensing systems it not only gathers positional and accelerational data but also senses muscle tension from several locations on each arm. The Conductor's Jacket was used to gather conducting data from six subjects, three professional conductors and three students, during twelve hours of rehearsals and performances. Analyses of the data yielded thirty-five significant features that seem to reflect intuitive and natural gestural tendencies, including context-based hand switching, anticipatory 'flatlining' effects, and correlations between respiration and phrasing. The results indicate that muscle tension and respiration signals reflect several significant and expressive characteristics of a conductor's gestures. From these results we present nine hypotheses about human musical expression, including ideas about efficiency, intentionality, polyphony, signal-to-noise ratios, and musical flow state. Finally, this thesis describes the Gesture Construction, a musical software system that analyzes and performs music in real-time based on the performer's gestures and breathing signals. A bank of software filters extracts several of the features that were found in the conductor study, including beat intensities and the alternation between arms. These features are then used to generate real-time expressive effects by shaping the beats, tempos, articulations, dynamics, and note lengths in a musical score.by Teresa Marrin Nakra.Ph.D

On the Recognition of Emotion from Physiological Data

This work encompasses several objectives, but is primarily concerned with an experiment where 33 participants were shown 32 slides in order to create ‗weakly induced emotions‘. Recordings of the participants‘ physiological state were taken as well as a self report of their emotional state. We then used an assortment of classifiers to predict emotional state from the recorded physiological signals, a process known as Physiological Pattern Recognition (PPR). We investigated techniques for recording, processing and extracting features from six different physiological signals: Electrocardiogram (ECG), Blood Volume Pulse (BVP), Galvanic Skin Response (GSR), Electromyography (EMG), for the corrugator muscle, skin temperature for the finger and respiratory rate. Improvements to the state of PPR emotion detection were made by allowing for 9 different weakly induced emotional states to be detected at nearly 65% accuracy. This is an improvement in the number of states readily detectable. The work presents many investigations into numerical feature extraction from physiological signals and has a chapter dedicated to collating and trialing facial electromyography techniques. There is also a hardware device we created to collect participant self reported emotional states which showed several improvements to experimental procedure

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level