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제안 방법
- the multi-touch cancellation problem. In this paper, a simple but highly accurate algorithm was introduced, which recovers the multi-touch values from differential sensing values. It can accurately recover not only the multi-touch positions but also the strength of the touches.
- In this paper, we propose a new method that can accurately detect multiple touches of very small areas and a range of touch strength levels. It employs a recovery algorithm that recovers all the original touch points accurately even in the case of the multi-touch cancellation problem.
- In this paper, we propose a touch position recovery algorithm with a differential sensing circuit. The rest of this paper is organized as follows.
- 8 depicts a flow chart of the proposed algorithm. The algorithm starts with a differential sensing step, which iteratively scans all RX lines of the TSP. Each sensed data sample is stored in the memory after the ADC.
- points. The proposed algorithm iteratively processes two data samples and accumulates the intermediate results throughout all the RX differential data over each TX line. One of the two data samples is the intermediate result calculated in the previous iteration, and the other data sample is the next differential data sample read from the memory.
- The proposed method consists of only an adder and a comparator, and therefore, it allows a low-cost chip implementation with a negligible area overhead. Simulation experiments have shown that the proposed recovery algorithm provides a high SNR gain of 52.
- 17 dB. The proposed method provides a higher SNR than the single-line sensing scheme, owing to its common noise cancellation ability. On the other hand, the proposed method performs better than the delta-integration method, since the proposed recovery algorithm can filter out the remaining noise and maintain the high-resolution sensing data.
- It can accurately recover not only the multi-touch positions but also the strength of the touches. The proposed method recovers the touched values by using the high- resolution ADC-sampled data. Therefore, it can provide a substantially higher accuracy than a previous method such as [14] without sacrificing the processing speed and the hardware cost.
- The remaining steps of the proposed algorithm are to find the peak values and to determine their positions as the touched points. The proposed algorithm iteratively processes two data samples and accumulates the intermediate results throughout all the RX differential data over each TX line.
- 18-µm CMOS process. To accurately evaluate its performance, we applied to the simulation the actual noise signals measured from a 23-inch commercial TSP. Fig.
- To evaluate the operation and the performance of the proposed method, we conducted extensive simulations by using an accurate TSP model with 9 TX lines and 16 RX lines. We drove pulse waves onto one TX line, and read out each pair of RX lines sequentially.
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