Design and Validation of a Minimal Complexity Algorithm for Stair Step Counting

Wearable sensors play a significant role for monitoring the functional ability of the elderly and in general, promoting active ageing. One of the relevant variables to be tracked is the number of stair steps (single stair steps) performed daily, which is more challenging than counting flight of stairs and detecting stair climbing. In this study, we proposed a minimal complexity algorithm composed of a hierarchical classifier and a linear model to estimate the number of stair steps performed during everyday activities. The algorithm was calibrated on accelerometer and barometer recordings measured using a sensor platform worn at the wrist from 20 healthy subjects. It was then tested on 10 older people, specifically enrolled for the study. The algorithm was then compared with other three state-of-the-art methods, which used the accelerometer, the barometer or both. The experiments showed the good performance of our algorithm (stair step counting error: 13.8%), comparable with the best state-of-the-art (p > 0.05), but using a lower computational load and model complexity. Finally, the algorithm was successfully implemented in a low-power smartwatch prototype with a memory footprint of about 4 kB

Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-antenna Dense Small Cell Networks

This paper studies the performance of cache-enabled dense small cell networks consisting of multi-antenna sub-6 GHz and millimeter-wave base stations. Different from the existing works which only consider a single antenna at each base station, the optimal content placement is unknown when the base stations have multiple antennas. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mmWave frequencies. The maximization of the successful content delivery probability is a challenging problem. To tackle it, we first propose a constrained cross-entropy algorithm which achieves the near-optimal solution with moderate complexity. We then develop another simple yet effective heuristic probabilistic content placement scheme, termed two-stair algorithm, which strikes a balance between caching the most popular contents and achieving content diversity. Numerical results demonstrate the superior performance of the constrained cross-entropy method and that the two-stair algorithm yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and mmWave systems reveal an interesting tradeoff between caching capacity and density for the mmWave system to achieve similar performance as the sub-6 GHz system.Comment: 14 pages; Accepted to appear in IEEE Transactions on Wireless Communication

Increasing the rate of datasets amenable to CTFFR_{FFR} and quantitative plaque analysis: Value of software for reducing stair-step artifacts demonstrated in photon-counting detector CT

PURPOSE To determine the value of an algorithm for reducing stair-step artifacts for advanced coronary analyses in sequential mode coronary CT angiography (CCTA). METHODS Forty patients undergoing sequential mode photon-counting detector CCTA with at least one stair-step artifact were included. Twenty patients (14 males; mean age 57±17years) with 45 segments showing stair-step artifacts and without atherosclerosis were included for CT$_{FFR}$ analysis. Twenty patients (20 males; mean age 74±13years) with 22 segments showing stair-step artifacts crossing an atherosclerotic plaque were included for quantitative plaque analysis. Artifacts were graded, and CT$_{FFR}$ and quantitative coronary plaque analyses were performed in standard reconstructions and in those reconstructed with a software (entitled ZeeFree) for artifact reduction. RESULTS Stair-step artifacts were significantly reduced in ZeeFree compared to standard reconstructions (p<0.05). In standard reconstructions, CT$_{FFR}$ was not feasible in 3/45 (7 %) segments but was feasible in all ZeeFree reconstructions. In 9/45 (20 %) segments without atherosclerosis, the ZeeFree algorithm led to a change of CT$_{FFR}$ values from pathologic in standard to physiologic values in ZeeFree reconstructions. In one segment (1/22, 5 %), quantitative plaque analysis was not feasible in standard but only in ZeeFree reconstruction. The mean overall plaque volume (111±60 mm$^{3}$), the calcific (77±47 mm$^{3}$), fibrotic (31±28 mm$^{3}$), and lipidic (4±3 mm$^{3}$) plaque components were higher in standard than in ZeeFree reconstructions (overall 75±50 mm$^{3}$, p<0.001; calcific 51±42 mm$^{3}$, p<0.001; fibrotic 22±19 mm$^{3}$, p<0.05; lipidic 3±3 mm$^{3}$, p=0.055). CONCLUSION Despite the lack of reference standard modalities for CT$_{FFR}$ and coronary plaque analysis, initial evidence indicates that an algorithm for reducing stair-step artifacts in sequential mode CCTA increases the rate and quality of datasets amenable to advanced coronary artery analysis, hereby potentially improving patient management

Stairs Detection for Enhancing Wheelchair Capabilities Based on Radar Sensors

Powered wheelchair users encounter barriers to their mobility everyday. Entering a building with non barrier-free areas can massively impact the user mobility related activities. There are a few commercial devices and some experimental that can climb stairs using for instance adaptive wheels with joints or caterpillar drive. These systems rely on the use for sensing and control. For safe automated obstacle crossing, a robust and environment invariant detection of the surrounding is necessary. Radar may prove to be a suitable sensor for its capability to handle harsh outdoor environmental conditions. In this paper, we introduce a mirror based two dimensional Frequency-Modulated Continuous-Wave (FMCW) radar scanner for stair detection. A radar image based stair dimensioning approach is presented and tested under laboratory and realistic conditions.Comment: 5 pages, Accepted and presented in 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE 2017

A polynomial algorithm for the k-cluster problem on interval graphs

This paper deals with the problem of finding, for a given graph and a given natural number k, a subgraph of k nodes with a maximum number of edges. This problem is known as the k-cluster problem and it is NP-hard on general graphs as well as on chordal graphs. In this paper, it is shown that the k-cluster problem is solvable in polynomial time on interval graphs. In particular, we present two polynomial time algorithms for the class of proper interval graphs and the class of general interval graphs, respectively. Both algorithms are based on a matrix representation for interval graphs. In contrast to representations used in most of the previous work, this matrix representation does not make use of the maximal cliques in the investigated graph.Comment: 12 pages, 5 figure

Hard and Easy Instances of L-Tromino Tilings

We study tilings of regions in the square lattice with L-shaped trominoes. Deciding the existence of a tiling with L-trominoes for an arbitrary region in general is NP-complete, nonetheless, we identify restrictions to the problem where it either remains NP-complete or has a polynomial time algorithm. First, we characterize the possibility of when an Aztec rectangle and an Aztec diamond has an L-tromino tiling. Then, we study tilings of arbitrary regions where only $180^\circ$ rotations of L-trominoes are available. For this particular case we show that deciding the existence of a tiling remains NP-complete; yet, if a region does not contains certain so-called "forbidden polyominoes" as sub-regions, then there exists a polynomial time algorithm for deciding a tiling.Comment: Full extended version of LNCS 11355:82-95 (WALCOM 2019