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The burgeoning demands for health care and human-machine interfaces call for the next generation of multifunctional integrated sensor systems with facile fabrication processes and reliable performances. Laser-induced graphene (LIG) with highly tunable physical and chemical characteristics plays vital roles in developing versatile skin-like flexible or stretchable sensor systems. This Progress Report presents an in-depth overview of the latest advances in LIG-based techniques in the applications of flexible sensors. First, the merits of the LIG technique are highlighted especially as the building blocks for flexible sensors, followed by the description of various fabrication methods of LIG and its variants. Then, the focus is moved to diverse LIG-based flexible sensors, including physical sensors, chemical sensors, and electrophysiological sensors. Mechanisms and advantages of LIG in these scenarios are described in detail. Furthermore, various representative paradigms of integrated LIG-based sensor systems are presented to show the capabilities of LIG technique for multipurpose applications. The signal cross-talk issues are discussed with possible strategies. The LIG technology with versatile functionalities coupled with other fabrication strategies will enable high-performance integrated sensor systems for next-generation skin electronics.

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As a reinforcement technology that improves load-bearing ability and prevents injuries, assisted exoskeleton robots have extensive applications in freight transport and health care. The perception of gait information by such robots is vital for their control. This information is the basis for motion planning in assistive and collaborative functions. Here, a wearable gait recognition sensor system for exoskeleton robots is presented. Pressure sensor arrays based on laser-induced graphene are developed with flexibility and reliability. Multiple sensor units are integrated into an insole to detect real-time pressure at key plantar positions. In addition, the circuit hardware and the algorithm are designed to reinforce the sensor system with the capability of gait recognition. The experimental results show that the accuracy of gait recognition by the proposed system is 99.85%, and the effectiveness of the system is further verified through testing on an exoskeleton robot.

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Thin film-based thermal flow sensors afford applications in healthcare and industries owing to their merits in preserving initial flow distributions. However, traditional thermal flow sensors are primarily applied to track flow intensities based on hot-wire or hot-film sensing mechanisms due to their relatively facile device configurations and fabrication strategies. Herein, a calorimetric thermal flow sensor is proposed based on laser direct writing to form laser-induced graphene as heaters and temperature sensors, resulting in monitoring both flow intensities and orientations. Via homogeneously surrounding spiral heaters with multiple temperature sensors, the device exhibits high sensitivity (∼162 K·s/m) at small flows with an extended flow detection range (∼25 m/s). Integrating the device with a data-acquisition board and a dual-mode graphical user interface enables wirelessly and dynamically monitoring respiration and the motion of robotic arms. This versatile flow sensor with facile manufacturing affords potentials in health inspection, remote monitoring, and studying hydrodynamics.

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Skin-like flexible sensors play vital roles in healthcare and human-machine interactions. However, general goals focus on pursuing intrinsic static and dynamic performance of skin-like sensors themselves accompanied with diverse trial-and-error attempts. Such a forward strategy almost isolates the design of sensors from resulting applications. Here, a machine learning (ML)-guided design of flexible tactile sensor system is reported, enabling a high classification accuracy (≈99.58%) of tactile perception in six dynamic touch modalities. Different from the intuition-driven sensor design, such ML-guided performance optimization is realized by introducing a support vector machine-based ML algorithm along with specific statistical criteria for fabrication parameters selection to excavate features deeply concealed in raw sensing data. This inverse design merges the statistical learning criteria into the design phase of sensing hardware, bridging the gap between the device structures and algorithms. Using the optimized tactile sensor, the high-quality recognizable signals in handwriting applications are obtained. Besides, with the additional data processing, a robot hand assembled with the sensor is able to complete real-time touch-decoding of an 11-digit braille phone number with high accuracy.

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BACKGROUND: Down syndrome (DS), also known as trisomy 21 (T21), is the most common genetic disorder associated with intellectual disability. There are two methods commonly used for prenatal testing of DS: serum screening (SS) for biomarkers in maternal serum and noninvasive prenatal testing (NIPT) for aneuploidy by cell-free DNA (cfDNA) in maternal plasma. However, cost-effectiveness analyses of these two methods are mostly based on data derived from simulations with various models, with theoretical values calculated. In this study, we statistically analyzed clinical DS screening data and pregnancy outcomes during the follow-up of pregnant women in Zhuhai City, China. The economics of the two mainstream prenatal DS screening methods was evaluated from a public health perspective. METHODS: A retrospective analysis was performed on the data of 17,363 pregnant women who received SS and NIPT during gestation in Zhuhai from 2018 to 2019, and a cost-effectiveness analysis was performed with four screening strategies. In strategy I, all pregnant women received SS, and those with T21 risk ≥1/270 had invasive prenatal diagnosis (IPD). In strategy II, all pregnant women received SS, those with T21 risk ≥ 1/270 had IPD, and those with 1/270 > T21 risk ≥ 1/1,000 had NIPT; then, women at high risk based on NIPT also had IPD. In strategy III, all pregnant women received SS, and those with T21 risk ≥1,000 had NIPT; then, women at high risk based on NIPT results had IPD. In strategy IV, all pregnant women received NIPT and those at high risk based on NIPT results had IPD. Finally, to assess the cost and effectiveness of DS screening, the total costs were calculated as the sum of screening and diagnosis as well as the direct and indirect economic burden during the average life cycle of DS patients. RESULTS: A total of 22 of the 17,363 (1/789) pregnant women had DS, of which only one woman was over 35 years of age. SS detected 1,024 cases at high risk of T21 (≥1/270), 8 cases were true positive, with a positive predictive value of 0.78% and a detection rate of 36.4%. NIPT detected 27 cases at high risk of T21 (Z ≥ 3) and 22 cases of DS, with a positive predictive value of 81.5% and a detection rate of 100%. Strategy I had the largest total cost of 65.54 million CNY, strategy II and III had similar total costs of 40 million CNY, and strategy IV had the lowest total cost of 14.91 million CNY. By comparison, the screening strategy with NIPT alone had the highest health economic value for DS. CONCLUSIONS: SS was greatly affected by nuchal translucency and the accuracy of gestational age measured by ultrasonography. Unstandardized ultrasonography was an important reason for the low DS detection rate with SS. The influence of interfering factors on NIPT was much lower than in SS. NIPT can be used as an alternative to SS and as a primary screening strategy of prenatal DS screening for secondary prevention and control of birth defects. NIPT greatly decreased the frequency of IPD and the miscarriages associated with IPD, saved the limited medical and health resources, and greatly increased DS detection rate. Therefore, NIPT has great social and economic benefits.

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OBJECTIVE: To discuss the advantages and technical limitations of various molecular genetic techniques in the diagnosis of two infants featuring all-round developmental retardation. METHODS: The two patients were initially screened by using chromosomal microarray analysis (CMA). For patient 1, his parents were also subjected to CMA analysis, and the data was analyzed by using ChAS and UPD-tool software. For patient 2, methylation-specific PCR (MS-PCR) was carried out. RESULTS: Patient 1 was diagnosed with maternal uniparental disomy (UPD) type Prader-Willi syndrome (PWS) by CMA and UPD-tool family analysis. His chromosomes 15 were of maternal UPD with homology/heterology. Patient 2 was diagnosed with deletion type PWS by combined CMA and MS-PCR. CONCLUSION: Correct selection of laboratory methods based on the advantages and limitations of various molecular techniques can help with diagnosis of genomic imprinting disorders and enable better treatment and prognosis through early intervention.

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OBJECTIVE: To diagnose a 46,XN,del(11)(q14q22) fetus by non-invasive prenatal testing (NIPT), karyotype analysis and whole genome sequencing (WGS). METHODS: Peripheral blood sample of the gravida was taken for NIPT screening. Blood samples of the gravida, her husband, and umbilical cord blood were also taken for chromosome karyotyping and whole genome sequencing (WGS). RESULTS: NIPT screening indicated the fetus has carried partial deletion of chromosome 11, while no chromosomal abnormality was found with the cord blood sample due to the low resolution of G-banding analysis. WGS analysis of the cord blood indicated 46,XN,del(11q14.3q22.1). seq[GRCh37/hg19] (90 623 404-97 469 319)×1, 6.85 Mb. The karyotype of the fetus was eventually determined as 46,XN,del(11)(q14q22). Karyotyping analysis suggested that the gravida and her husband were 46,XX,del(11)(q14q22)[8]/46,XX[92] and 46,XY, respectively. However, neither of them was found to harbor the del(11)(q14q22) by WGS. CONCLUSION: The abnormal karyotype of the fetus has derived from its mother's low percentage mosaicism. Combined NIPT, karyotyping analysis and WGS can detect chromosomal disorders with accuracy.

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OBJECTIVE: To analyze a fetus with abnormal cardiac ultrasound by using various techniques and explore its genotype-phenotype correlation. METHODS: Lymphocytes derived from umbilical cord blood sample were subjected to G-banding analysis. Short tandem repeats quantitative fluorescence PCR (STR-QF-PCR) was used for analysis of fetal DNA as an auxiliary test. Low-coverage whole genome sequencing (WGS) was used to detect chromosomal deletion/duplication which exceeded 100 kb in size. RESULTS: The karyotype of the fetus was 47,XN,+mar. As detected by STR-QF-PCR, the copy number of GATA178F11 locus on chromosome 18 was 4, and the duplicated fragment was derived from the mother. WGS suggested that the fetus to be 46,XN,dup(18p11.21p11.32).seq [GRCh37/hg19](10 001-15 378 887)× 4, with the duplicated fragment spanning approximately 15.38 Mb. CONCLUSION: The cardiac malformation of the fetus may be attributed to the partial duplication of chromosome 18p. Combined cytogenetic and molecular methods can facilitate prenatal detection of genetic abnormalities.

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