IEEE RESEARCH PAPER ON SKINPUT TECHNOLOGY

Enter the email address you signed up with and we’ll email you a reset link. When an intensity threshold was exceeded, the program recorded the timestamp as a potential start of a tap. In general, tapping on soft regions of the arm creates higher amplitude transverse waves than tapping on boney areas e. To overcome these challenges, the idea of a single sensing element with a flat response curve, to an array of highly tuned vibration sensors was dropped. Inspection of the confusion matrices showed no systematic errors in the classification, with errors tending to be evenly distributed over the other digits. Ramchandra, Head of the Department, for giving me a chance to present this seminar.

Researchers have harnessed the electrical signals generated by muscle activation during normal hand movement through electromyography EMG. Segmentation, as in other conditions, was essentially perfect. Foremost, most mechanical sensors are engineered to provide relatively flat response curves over the range of frequencies that is relevant to our signal. This search revealed one plausible, although irregular, layout with high accuracy at six input locations. In contrast, brain signals have been harnessed as a direct input for use by paralyzed patients, but direct brain computer interfaces BCIs still lacks the bandwidth required for everyday computing tasks, and require levels of focus, training, and concentration that are incompatible with typical computer interaction. Log In Sign Up.

Skinput leverages the natural acoustic conduction properties of the reesarch body to provide an input system, and is thus related to previous work in the use of biological signals for computer input. Foremost, most mechanical sensors are engineered to provide relatively flat response curves over the range of frequencies that is relevant to our signal.

For example, the ATmega processor employed by the Arduino platform can sample analog readings at 77 kHz with no loss of precision, and could therefore provide the full sampling power required for Skinput 55 kHz total.

ieee research paper on skinput technology

Additionally, the cantilevered sensors were naturally insensitive to forces parallel to the skin e. This effect was more prominent laterally than longitudinally. This stage requires the collection of several examples for each input location of interest.

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Ieee research paper on skinput technology – Google Docs

In particular, resolves the location of finger tips on the arm and hand by analyzing mechanical vibrations that propagate through the body. When the sensor was placed below the elbow, on the forearm, one package was located near the Radius, tschnology bone that runs from the lateral side of the elbow to the thumb side of the wrist, and the other near the Ulna, which runs parallel to this on the medial side of the arm closest to the body.

Similarly, we also believe that joints play an important role in making tapped locations acoustically distinct. When an intensity threshold was exceeded, the program recorded the timestamp as a potential start of a tap.

ieee research paper on skinput technology

These, however, are computationally expensive and error prone in mobile scenarios where, e. While bone conduction microphones might seem a suitable choice for Skinput, these devices are typically engineered for capturing human voice, and filter out energy below the range of human speech whose lowest frequency is around 85Hz. Once an input is classified, an event associated with that location is instantiated.

Skinput: appropriating the body as an input surface – Semantic Scholar

Each location thus provided slightly different acoustic coverage papfr information, helpful in disambiguating input location. Conversely, we tuned the lower sensor array to be sensitive to higher frequencies, in order to better capture signals transmitted though denser bones. Skibput approach is feasible, but suffers from serious occlusion and accuracy limitations. This reduced sample rate and consequently low processing bandwidth makes our technique readily portable to embedded processors.

First, it provided a live visualization of the data from our ten sensors, which was useful in identifying acoustic features. Enter the email address you signed up with and we’ll email you a reset link. Finally, bone conduction microphones and headphones now common consumer technologies – represent an skinpt bio- sensing technology that is relevant to the present work.

Skinput: appropriating the body as an input surface

Classification accuracy for the ten-location forearm condition stood at For example, describes a technique that allows a small mobile device to turn tables on which it rests into a gestural finger input canvas. In contrast, brain signals have been harnessed as a direct input for use by paralyzed patients, but direct brain computer interfaces BCIs still lacks the bandwidth required for everyday computing tasks, and require levels of focus, training, and concentration that are incompatible with typical computer interaction.

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ieee research paper on skinput technology

This approach provides an always available, naturally portable, and on-body finger input system. When shot with a high- speed camera, these appear as ripples, which propagate outward from the point of contact see video. To further illustrate the utility of our approach, we conclude with several proof-of-concept applications we developed. I take this opportunity to express my gratitude to the people who have been instrumental in the successful completion of this report.

These are fed into the trained SVM for classification.

Click here to sign up. This is unsurprising given the morphology of the arm, with a high degree of bilateral symmetry along the long axis.

This is almost certainly related to the acoustic loss at the elbow joint and the additional 10cm of distance between the sensor and input targets.

After an input has been segmented, the waveforms are analyzed. One option is to opportunistically appropriate surface area from the environment for interactive purposes. Then we will describe the Skinput sensor and the processing techniques we use to segment, analyze, and classify bio-acoustic signals.

Some energy is radiated into the air as sound waves; this energy is not captured by the Skinput system. We conclude with descriptions of several prototype applications that demonstrate the rich design space we believe Skinput enables. Data was then sent from our thin reseearch over a local socket to our primary application, written in Java.

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