Wearable Sensors for Monitoring Human Motion: A Review on Mechanisms, Materials, and Challenges

The emergence of flexible wearable electronics as a new platform for accurate, unobtrusive, user-friendly, and longitudinal sensing has opened new horizons for personalized assistive tools for monitoring human locomotion and physiological signals. Herein, we survey recent advances in methodologies and materials involved in unobtrusively sensing a medium to large range of applied pressures and motions, such as those encountered in large-scale body and limb movements or posture detection. We discuss three commonly used methodologies in human gait studies: inertial, optical, and angular sensors. Next, we survey the various kinds of electromechanical devices (piezoresistive, piezoelectric, capacitive, triboelectric, and transistive) that are incorporated into these sensor systems; define the key metrics used to quantitate, compare, and optimize the efficiency of these technologies; and highlight state-of-the-art examples. In the end, we provide the readers with guidelines and perspectives to address the current challenges of the field.

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Near-Linear Responsive and Wide-Range Pressure and Stretch Sensor Based on Hierarchical Graphene-Based Structures via Solvent-Free Preparation

Polymers ◽

10.3390/polym12081814 ◽

2020 ◽

Vol 12 (8) ◽

pp. 1814 ◽

Cited By ~ 1

Author(s):

Jian Wang ◽

Ryuki Suzuki ◽

Kentaro Ogata ◽

Takuto Nakamura ◽

Aixue Dong ◽

...

Keyword(s):

Organic Solvents ◽

Large Strain ◽

Rapid Development ◽

Wearable Sensors ◽

Human Motion ◽

Solvent Free ◽

Gauge Factor ◽

Wearable Electronics ◽

Human Motion Detection ◽

Wide Range

Flexible and wearable electronics have huge potential applications in human motion detection, human–computer interaction, and context identification, which have promoted the rapid development of flexible sensors. So far the sensor manufacturing techniques are complex and require a large number of organic solvents, which are harmful not only to human health but also to the environment. Here, we propose a facile solvent-free preparation toward a flexible pressure and stretch sensor based on a hierarchical layer of graphene nanoplates. The resulting sensor exhibits many merits, including near-linear response, low strain detection limits to 0.1%, large strain gauge factor up to 36.2, and excellent cyclic stability withstanding more than 1000 cycles. Besides, the sensor has an extraordinary pressure range as large as 700 kPa. Compared to most of the reported graphene-based sensors, this work uses a completely environmental-friendly method that does not contain any organic solvents. Moreover, the sensor can practically realize the delicate detection of human body activity, speech recognition, and handwriting recognition, demonstrating a huge potential for wearable sensors.

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Highly Sensitive and Stretchable c-MWCNTs/PPy Embedded Multidirectional Strain Sensor Based on Double Elastic Fabric for Human Motion Detection

Nanomaterials ◽

10.3390/nano11092333 ◽

2021 ◽

Vol 11 (9) ◽

pp. 2333

Author(s):

Huiying Shen ◽

Huizhen Ke ◽

Jingdong Feng ◽

Chenyu Jiang ◽

Qufu Wei ◽

...

Keyword(s):

Degrees Of Freedom ◽

Large Scale ◽

Strain Sensor ◽

High Sensitivity ◽

Human Motion ◽

Strain Sensors ◽

Gauge Factor ◽

Wearable Electronics ◽

Synovial Joint ◽

Human Motion Detection

Owing to the multi-dimensional complexity of human motions, traditional uniaxial strain sensors lack the accuracy in monitoring dynamic body motions working in different directions, thus multidirectional strain sensors with excellent electromechanical performance are urgently in need. Towards this goal, in this work, a stretchable biaxial strain sensor based on double elastic fabric (DEF) was developed by incorporating carboxylic multi-walled carbon nanotubes(c-MWCNTs) and polypyrrole (PPy) into fabric through simple, scalable soaking and adsorption-oxidizing methods. The fabricated DEF/c-MWCNTs/PPy strain sensor exhibited outstanding anisotropic strain sensing performance, including relatively high sensitivity with the maximum gauge factor (GF) of 5.2, good stretchability of over 80%, fast response time < 100 ms, favorable electromechanical stability, and durability for over 800 stretching–releasing cycles. Moreover, applications of DEF/c-MWCNTs/PPy strain sensor for wearable devices were also reported, which were used for detecting human subtle motions and dynamic large-scale motions. The unconventional applications of DEF/c-MWCNTs/PPy strain sensor were also demonstrated by monitoring complex multi-degrees-of-freedom synovial joint motions of human body, such as neck and shoulder movements, suggesting that such materials showed a great potential to be applied in wearable electronics and personal healthcare monitoring.

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Self-Powered Smart Insole for Monitoring Human Gait Signals

Sensors ◽

10.3390/s19245336 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5336 ◽

Cited By ~ 3

Author(s):

Wei Wang ◽

Junyi Cao ◽

Jian Yu ◽

Rong Liu ◽

Chris R. Bowen ◽

...

Keyword(s):

Vinylidene Fluoride ◽

Rapid Development ◽

Human Motion ◽

Multiscale Entropy ◽

Human Gait ◽

Pvdf Film ◽

Aluminum Electrode ◽

Wearable Electronics ◽

Motion Speed ◽

Self Powered

With the rapid development of low-power consumption wireless sensors and wearable electronics, harvesting energy from human motion to enable self-powered sensing is becoming desirable. Herein, a pair of smart insoles integrated with piezoelectric poly(vinylidene fluoride) (PVDF) nanogenerators (NGs) are fabricated to simultaneously harvest energy from human motion and monitor human gait signals. Multi-target magnetron sputtering technology is applied to form the aluminum electrode layers on the surface of the PVDF film and the self-powered insoles are fabricated through advanced 3D seamless flat-bed knitting technology. Output responses of the NGs are measured at different motion speeds and a maximum value of 41 V is obtained, corresponding to an output power of 168.1 μW. By connecting one NG with an external circuit, the influence of external resistance, capacitor, and motion speed on the charging characteristics of the system is systematically investigated. To demonstrate the potential of the smart insoles for monitoring human gait signals, two subjects were asked to walk on a treadmill at different speeds or with a limp. The results show that one can clearly distinguish walking with a limp from regular slow, normal, and fast walking states by using multiscale entropy analysis of the stride intervals.

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Toward optimal fingerprint indexing for large scale genomics

10.1101/2021.11.04.467355 ◽

2021 ◽

Author(s):

Clement Agret ◽

Bastien Cazaux ◽

Antoine Limasset

Keyword(s):

Large Scale ◽

State Of The Art ◽

False Positive Rate ◽

Bacterial Genomes ◽

Genomic Databases ◽

Novel Structure ◽

Fingerprint Indexing ◽

Positive Rate ◽

Inverted Indexes ◽

User Friendly

Motivation: To keep up with the scale of genomic databases, several methods rely on local sensitive hashing methods to efficiently find potential matches within large genome collections. Existing solutions rely on Minhash or Hyperloglog fingerprints and require reading the whole index to perform a query. Such solutions can not be considered scalable with the growing amount of documents to index. Results: We present NIQKI, a novel structure using well-designed fingerprints that lead to theoretical and practical query time improvements, outperforming state-of-the-art by orders of magnitude. Our contribution is threefold. First, we generalize the concept of Hyperminhash fingerprints in (h,m)-HMH fingerprints that can be tuned to present the lowest false positive rate given the expected sub-sampling applied. Second, we provide a structure able to index any kind of fingerprints based on inverted indexes that provide optimal queries, namely linear with the size of the output. Third, we implemented these approaches in a tool dubbed NIQKI that can index and calculate pairwise distances for over one million bacterial genomes from GenBank in a matter of days on a small cluster. We show that our approach can be orders of magnitude faster than state-of-the-art with comparable precision. We believe that this approach can lead to tremendous improvement allowing fast query, scaling on extensive genomic databases. Availability and implementation: We wrote the NIQKI index as an open-source C++ library under the AGPL3 license available at https://github.com/Malfoy/ NIQKI. It is designed as a user-friendly tool and comes along with usage sample

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Multiple-Joint Pedestrian Tracking Using Periodic Models

Sensors ◽

10.3390/s20236917 ◽

2020 ◽

Vol 20 (23) ◽

pp. 6917

Author(s):

Marzieh Dolatabadi ◽

Jos Elfring ◽

René van de Molengraft

Keyword(s):

State Of The Art ◽

Human Motion ◽

Human Gait ◽

Proof Of Concept ◽

Pedestrian Tracking ◽

Motion Patterns ◽

Autonomous Cars ◽

Periodic Models ◽

Institute Of Technology ◽

Karlsruhe Institute

Estimating accurate positions of multiple pedestrians is a critical task in robotics and autonomous cars. We propose a tracker based on typical human motion patterns to track multiple pedestrians. This paper assumes that the legs’ reflection and extension angles are approximately changing periodically during human motion. A Fourier series is fitted in order to describe the moving, such as describing the position and velocity of the hip, knee, and ankle. Our tracker receives the position of the ankle, knee, and hip as measurements. As a proof of concept, we compare our tracker with state-of-the-art methods. The proposed models have been validated by experimental data, the Human Gait Database (HuGaDB), and the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) tracking benchmark. The results indicate that our tracker is able to estimate the reflection and extension angles with a precision of 90.97%. Moreover, the comparison shows that the tracking precision increases up to 1.3% with the proposed tracker when compared to a constant velocity based tracker.

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Dry-Coated Graphite onto Sandpaper for Triboelectric Nanogenerator as an Active Power Source for Portable Electronics

Nanomaterials ◽

10.3390/nano9111585 ◽

2019 ◽

Vol 9 (11) ◽

pp. 1585 ◽

Cited By ~ 3

Author(s):

Smitha Ankanahalli Shankaregowda ◽

Rumana Farheen Sagade Muktar Ahmed ◽

Yu Liu ◽

Chandrashekar Bananakere Nanjegowda ◽

Xing Cheng ◽

...

Keyword(s):

Large Scale ◽

Liquid Crystal Display ◽

Short Circuit ◽

Bottom Layer ◽

Human Motion ◽

Open Circuit ◽

Triboelectric Nanogenerator ◽

Portable Devices ◽

Wearable Electronics ◽

Dry Electrode

Developing an eco-friendly, flexible and recyclable micro-structured dry electrode for sustainable life is essential. In this work, we have developed irregular, micro-structured sandpaper coated with graphite powder as an electrode for developing a simple, low-cost, contact-separation mode graphite-coated sandpaper-based triboelectric nanogenerator (GS-TENG) as a self-powered device and biomechanical sensor. The as-fabricated GS-TENG is a dielectric-conductor model. It is made up of a bottom layer with polytetrafluoroethylene (PTFE) as a triboelectric layer, which is attached onto a graphite-coated sandpaper-based electrode and a top layer with aluminum as another triboelectric layer as well as an electrode. The forward and reverse open-circuit voltages reach upto ~33.8 V and ~36.62 V respectively, and the forward and reverse short-circuit currents are ~2.16 µA and ~2.17µA, respectively. The output generated by GS-TENG can power 120 blue light-emitting diodes connected in series, liquid crystal display and can charge commercial capacitors along with the rectifier circuit. The capacitor of 22 µF is charged upto 5 V and is sufficient to drive digital watch as wearable electronics. Moreover, the device can track signals generated by human motion, hence it scavenges biomechanical energy. Thus, GS-TENG facilitates large-scale fabrication and has potential for future applications in wearable and portable devices.

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From human motion capture to humanoid locomotion imitation Application to the robots HRP-2 and HOAP-3

Robotica ◽

10.1017/s0263574710000172 ◽

2010 ◽

Vol 29 (2) ◽

pp. 325-334 ◽

Cited By ~ 14

Author(s):

Luc Boutin ◽

Antoine Eon ◽

Said Zeghloul ◽

Patrick Lacouture

Keyword(s):

Motion Capture ◽

Human Locomotion ◽

Inverse Kinematic ◽

Human Motion ◽

Simulation Software ◽

Body Motion ◽

Whole Body ◽

Human Gait ◽

Reference Trajectory ◽

Double Support

SUMMARYThis paper presents a method to generate humanoid gaits from a human locomotion pattern recorded by a motion capture system. Thirty seven reflective markers were fixed on the human subject skin in order to get the subject whole body motion. To reproduce the human gait, especially the toes and heel contacts, the front and back edges of the robot's feet are used as support at the start and the end of the double support phase. The balance of the robot is respected using the zero moment point (ZMP) criterion and confirmed by the simulation software OPENHRP (General Robotics, Inc®). First, the feet trajectory as well as the ZMP reference trajectory are defined from the motion of the robot controlled as a marionette with the measured human joint angles. Then a specific inverse kinematic (IK) algorithm is proposed to find the humanoid robot's joint trajectories respecting the constraints of balance, floor contacts, and joint limits. The studied motion presented in this paper is a human walking trajectory containing a start, a movement in a straight line, a stop, and a quarter turn. The method was developed to be easily used for human-like robots of different sizes, masses, and structures and has been tested on the robot HRP-2 (AIST, Kawada Industries, Inc®) and on the small-sized humanoid robot HOAP-3 (Fujitsu Automation Ltd®).

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Fiber-Based Sensors and Energy Systems for Wearable Electronics

Applied Sciences ◽

10.3390/app11020531 ◽

2021 ◽

Vol 11 (2) ◽

pp. 531

Author(s):

Jungjoon Lee ◽

Sungha Jeon ◽

Hyeonyeob Seo ◽

Jung Tae Lee ◽

Seongjun Park

Keyword(s):

Storage Systems ◽

Wearable Sensors ◽

Wearable Devices ◽

Environmental Scanning ◽

Wearable Electronics ◽

Biomedical Sensors ◽

Safety And Health ◽

External Power Source ◽

Self Powered ◽

User Friendly

Wearable electronics have been receiving increasing attention for the past few decades. Particularly, fiber-based electronics are considered to be ideal for many applications for their flexibility, lightweight, breathability, and comfortability. Furthermore, fibers and fiber-based textiles can be 3D-molded with ease and potentially integrated with everyday clothes or accessories. These properties are especially desired in the fields of bio-related sensors and energy-storage systems. Wearable sensors utilize a tight interface with human skin and clothes for continuous environmental scanning and non-invasive health monitoring. At the same time, their flexible and lightweight properties allow more convenient and user-friendly experiences to the wearers. Similarly, for the wearable devices to be more accessible, it is crucial to incorporate energy harvesting and storage systems into the device themselves, removing the need to attach an external power source. This review summarizes the recent applications of fibers and fiber-based textiles in mechanical, photonic, and biomedical sensors. Pressure and strain sensors and their implementation as electronic skins will be explored, along with other various fiber sensors capable of imaging objects or monitoring safety and health markers. In addition, we attempt to elucidate recent studies in energy-storing fibers and their implication in self-powered and fully wireless wearable devices.

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