Bloorview Research Institute, Bloorview Kids Rehab and the Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
Physiol Meas. 2010 Jan;31(1):N1-9. doi: 10.1088/0967-3334/31/1/N01. Epub 2009 Nov 26.
Dual-axis swallowing accelerometry is an emerging tool for the assessment of dysphagia (swallowing difficulties). These signals however can be very noisy as a result of physiological and motion artifacts. In this note, we propose a novel scheme for denoising those signals, i.e. a computationally efficient search for the optimal denoising threshold within a reduced wavelet subspace. To determine a viable subspace, the algorithm relies on the minimum value of the estimated upper bound for the reconstruction error. A numerical analysis of the proposed scheme using synthetic test signals demonstrated that the proposed scheme is computationally more efficient than minimum noiseless description length (MNDL)-based denoising. It also yields smaller reconstruction errors than MNDL, SURE and Donoho denoising methods. When applied to dual-axis swallowing accelerometry signals, the proposed scheme exhibits improved performance for dry, wet and wet chin tuck swallows. These results are important for the further development of medical devices based on dual-axis swallowing accelerometry signals.
双轴吞咽加速计是评估吞咽困难（吞咽障碍）的一种新兴工具。然而，由于生理和运动伪影的影响，这些信号可能非常嘈杂。在本说明中，我们提出了一种新颖的方案来对这些信号进行去噪，即在减少的小波子空间内寻找最优去噪阈值的计算效率搜索。为了确定可行的子空间，该算法依赖于重建误差的估计上界的最小值。使用合成测试信号对所提出方案的数值分析表明，与基于最小无噪声描述长度 (MNDL) 的去噪相比，所提出的方案在计算上更有效。它产生的重建误差也小于 MNDL、SURE 和 Donoho 去噪方法。当应用于双轴吞咽加速计信号时，所提出的方案在干、湿和湿下巴托吞咽时表现出更好的性能。这些结果对于基于双轴吞咽加速计信号的医疗设备的进一步发展非常重要。
