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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (15 August 2023) | Viewed by 32528

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Special Issue Editor

Dr. Oren Tirosh

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School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
Interests: sport science; gait analysis; posture; balance; rehabilitation

Special Issue Information

Dear Colleagues,

Wearable sensor technology has created a portable and low-cost opportunity for the analysis of human movement in both clinical and sport settings. For example, inertial measurement units (IMU) are used to identify ground impact in running and assist in providing biofeedback intervention to reduce the risk of tibia stress fracture. Inertia and pressure sensors embedded in sport equipment, such as in cricket ball and soccer boot, are used to identify ball spin and player performance in bowling and kicking. Recently, the use of IMU sensors to identify surgeon performance in the theatre has been suggested.

Motion sensors embedded in smartphones provide opportunities for remote monitoring of movement impairment. The use of smartphones to identify gait and posture impairments has been suggested in populations with neurological disorders, older adults, and those at risk of falls. Global acceptance of smartphones as medical devices has become an unprecedented challenge among clinical researchers.

This Special Issue aims to explore original developments and the use of wearable sensors to assess and monitor human movement in both clinical and sport applications. The issue welcomes contributions of original research papers and reviews focusing on wearable sensors for assessing and monitoring human movement. Submissions should address the use of sensors for health and sport performance, which might include but is not limited to the following topics:

Wearable motion and pressure sensors for performance analysis in sport;
Wearable motion and pressure sensors for diagnosis, training, and interventions in health and sport;
Smartphone sensors for gait and posture analysis;
Textile sensors for gait and posture;
Wearable computing for health and sport;
Mobile movement applications for health and sport;
Wearables for ergonomics.

Dr. Oren Tirosh
Guest Editor

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Keywords

Wearables for human movement
Wearable motion sensors
Wearable pressure sensors
Wearable sensors
Wearable for rehabilitation
Textile sensors for human movement
Smartphones motion sensors
Smartphones for human movement

Published Papers (11 papers)

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24 pages, 9447 KiB

Open AccessArticle

Identification, Taxonomy and Performance Assessment of Type 1 and Type 2 Spin Bowling Deliveries with a Smart Cricket Ball

by René E. D. Ferdinands, Batdelger Doljin and Franz Konstantin Fuss

Sensors 2023, 23(18), 8012; https://doi.org/10.3390/s23188012 - 21 Sep 2023

Viewed by 1800

Abstract

Spin bowling deliveries in cricket, finger spin and wrist spin, are usually (Type 1, T1) performed with forearm supination and pronation, respectively, but can also be executed with opposite movements (Type 2, T2), specifically forearm pronation and supination, respectively. The aim of this study is to identify the differences between T1 and T2 using an advanced smart cricket ball, as well as to assess the dynamics of T1 and T2. With the hand aligned to the ball’s coordinate system, the angular velocity vector, specifically the x-, y- and z-components of its unit vector and its yaw and pitch angles, were used to identify time windows where T1 and T2 deliveries were clearly separated. Such a window was found 0.44 s before the peak torque, and maximum separation was achieved when plotting the y-component against the z-component of the unit vector, or the yaw angle against the pitch angle. In terms of physical performance, T1 deliveries are easier to bowl than T2; in terms of skill performance, wrist spin deliveries are easier to bowl than finger spin. Because the smart ball allows differentiation between T1 and T2 deliveries, it is an ideal tool for talent identification and improving performance through more efficient training. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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16 pages, 2430 KiB

Open AccessArticle

The Use of Wearable Inertial Sensors and Workplace-Based Exercises to Reduce Lateral Epicondylitis in the Workstation of a Textile Logistics Center

by Florian Michaud, Roberto Pazos, Urbano Lugrís and Javier Cuadrado

Sensors 2023, 23(11), 5116; https://doi.org/10.3390/s23115116 - 27 May 2023

Cited by 1 | Viewed by 1922

Abstract

People whose jobs involve repetitive motions of the wrist and forearm can suffer from lateral epicondylitis, which is a significant burden on both the individual and the employer due to treatment costs, reduced productivity, and work absenteeism. This paper describes an ergonomic intervention to reduce lateral epicondylitis in the workstation of a textile logistics center. The intervention includes workplace-based exercise programs, evaluation of risk factors, and movement correction. An injury- and subject-specific score was calculated from the motion captured with wearable inertial sensors at the workplace to evaluate the risk factors of 93 workers. Then, a new working movement was adapted to the workplace, which limited the observed risk factors and took into account the subject-specific physical abilities. The movement was taught to the workers during personalized sessions. The risk factors of 27 workers were evaluated again after the intervention to validate the effectiveness of the movement correction. In addition, active warm-up and stretching programs were introduced as part of the workday to promote muscle endurance and improve resistance to repetitive stress. The present strategy offered good results at low cost, without any physical modification of the workplace and without any detriment to productivity. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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19 pages, 2158 KiB

Open AccessArticle

Application-Layer Time Synchronization and Data Alignment Method for Multichannel Biosignal Sensors Using BLE Protocol

by Jianan Li, Eric Quintin, He Wang, Benjamin E. McDonald, Todd R. Farrell, Xinming Huang and Edward A. Clancy

Sensors 2023, 23(8), 3954; https://doi.org/10.3390/s23083954 - 13 Apr 2023

Cited by 1 | Viewed by 1904

Abstract

Wearable wireless biomedical sensors have emerged as a rapidly growing research field. For many biomedical signals, multiple sensors distributed about the body without local wired connections are required. However, designing multisite systems at low cost with low latency and high precision time synchronization of acquired data is an unsolved problem. Current solutions use custom wireless protocols or extra hardware for synchronization, forming custom systems with high power consumption that prohibit migration between commercial microcontrollers. We aimed to develop a better solution. We successfully developed a low-latency, Bluetooth low energy (BLE)-based data alignment method, implemented in the BLE application layer, making it transferable between manufacturer devices. The time synchronization method was tested on two commercial BLE platforms by inputting common sinusoidal input signals (over a range of frequencies) to evaluate time alignment performance between two independent peripheral nodes. Our best time synchronization and data alignment method achieved absolute time differences of 69 ± 71 μs for a Texas Instruments (TI) platform and 477 ± 490 μs for a Nordic platform. Their 95th percentile absolute errors were more comparable—under 1.8 ms for each. Our method is transferable between commercial microcontrollers and is sufficient for many biomedical applications. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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13 pages, 7210 KiB

Open AccessArticle

Human Arm Workout Classification by Arm Sleeve Device Based on Machine Learning Algorithms

by Sehwan Chun, Sangun Kim and Jooyong Kim

Sensors 2023, 23(6), 3106; https://doi.org/10.3390/s23063106 - 14 Mar 2023

Cited by 3 | Viewed by 3531

Abstract

Wearables have been applied in the field of fitness in recent years to monitor human muscles by recording electromyographic (EMG) signals. Understanding muscle activation during exercise routines allows strength athletes to achieve the best results. Hydrogels, which are widely used as wet electrodes in the fitness field, are not an option for wearable devices due to their characteristics of being disposable and skin-adhesion. Therefore, a lot of research has been conducted on the development of dry electrodes that can replace hydrogels. In this study, to make it wearable, neoprene was impregnated with high-purity SWCNTs to develop a dry electrode with less noise than hydrogel. Due to the impact of COVID-19, the demand for workouts to improve muscle strength, such as home gyms and personal trainers (PT), has increased. Although there are many studies related to aerobic exercise, there is a lack of wearable devices that can assist in improving muscle strength. This pilot study proposed the development of a wearable device in the form of an arm sleeve that can monitor muscle activity by recording EMG signals of the arm using nine textile-based sensors. In addition, some machine learning models were used to classify three arm target movements such as wrist curl, biceps curl, and dumbbell kickback from the EMG signals recorded by fiber-based sensors. The results obtained show that the EMG signal recorded by the proposed electrode contains less noise compared to that collected by the wet electrode. This was also evidenced by the high accuracy of the classification model used to classify the three arms workouts. This work classification device is an essential step towards wearable devices that can replace next-generation PT. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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19 pages, 2049 KiB

Open AccessArticle

Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol

by He Wang, Jianan Li, Benjamin E. McDonald, Todd R. Farrell, Xinming Huang and Edward A. Clancy

Sensors 2023, 23(5), 2465; https://doi.org/10.3390/s23052465 - 23 Feb 2023

Cited by 4 | Viewed by 1795

Abstract

Wireless wearable sensor systems for biomedical signal acquisition have developed rapidly in recent years. Multiple sensors are often deployed for monitoring common bioelectric signals, such as EEG (electroencephalogram), ECG (electrocardiogram), and EMG (electromyogram). Compared with ZigBee and low-power Wi-Fi, Bluetooth Low Energy (BLE) can be a more suitable wireless protocol for such systems. However, current time synchronization methods for BLE multi-channel systems, via either BLE beacon transmissions or additional hardware, cannot satisfy the requirements of high throughput with low latency, transferability between commercial devices, and low energy consumption. We developed a time synchronization and simple data alignment (SDA) algorithm, which was implemented in the BLE application layer without the need for additional hardware. We further developed a linear interpolation data alignment (LIDA) algorithm to improve upon SDA. We tested our algorithms using sinusoidal input signals at different frequencies (10 to 210 Hz in increments of 20 Hz—frequencies spanning much of the relevant range of EEG, ECG, and EMG signals) on Texas Instruments (TI) CC26XX family devices, with two peripheral nodes communicating with one central node. The analysis was performed offline. The lowest average (±standard deviation) absolute time alignment error between the two peripheral nodes achieved by the SDA algorithm was 384.3 ± 386.5 μs, while that of the LIDA algorithm was 189.9 ± 204.7 μs. For all sinusoidal frequencies tested, the performance of LIDA was always statistically better than that of SDA. These average alignment errors were quite low—well below one sample period for commonly acquired bioelectric signals. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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16 pages, 3587 KiB

Open AccessArticle

Pressure Sensors for Measuring the Grip Pressure during Kendo Attacks: Assessment of Laterality and Evidence of the Five Phases of Attack

by Kwangyul Jeong, Adin Ming Tan, Takeshi Asai, Kunihide Koda and Franz Konstantin Fuss

Sensors 2023, 23(3), 1189; https://doi.org/10.3390/s23031189 - 20 Jan 2023

Cited by 1 | Viewed by 3491

Abstract

In Kendo, there is no consensus as to which hand should produce more pressure when attacking the opponent with the bamboo sword, let alone how to teach the pressure distribution during coaching. There is the theory that a Kendo attack can be divided into five phases, which has not entered the coaching practice, either. The aim of this study was to measure the grip pressure during Kendo attacks, investigate the pressure distribution between the two hands, and find evidence for the existence of the alleged five attack phases. We instrumented a bamboo sword with grip pressure sensors and investigated the grip pressure in 23 participants. In all attack targets and in both hands, the pressure across all attack phases was significantly different. In general, the left-hand pressure was consistently and significantly higher than the right-hand one, across all five attack phases, for the hand, head, and flank attack targets. The surprising exception was the throat target with only two attack phases, the strike phase of which showed a greater pressure in the right hand. Across all participants, the left-hand pressure was greater in 60.22–100% in any phase of the four attack targets, except for the strike phase of the throat target. Through these results, we could verify the effect of the teaching customs in Kendo, as well as provide first-time evidence of the existence of the five attack phases. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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13 pages, 2333 KiB

Open AccessArticle

Validity and Reliability of a Novel Smartphone Tele-Assessment Solution for Quantifying Hip Range of Motion

by Charlotte J. Marshall, Doa El-Ansary, Adrian Pranata, Charlotte Ganderton, John O’Donnell, Amir Takla, Phong Tran, Nilmini Wickramasinghe and Oren Tirosh

Sensors 2022, 22(21), 8154; https://doi.org/10.3390/s22218154 - 25 Oct 2022

Cited by 3 | Viewed by 2247

Abstract

Background: Tele-health has become a major mode of delivery in patient care, with increasing interest in the use of tele-platforms for remote patient assessment. The use of smartphone technology to measure hip range of motion has been reported previously, with good to excellent validity and reliability. However, these smartphone applications did not provide real-time tele-assessment functionality. We developed a novel smartphone application, the TelePhysio app, which allows the clinician to remotely connect to the patient’s device and measure their hip range of motion in real time. The aim of this study was to investigate the concurrent validity and between-sessions reliability of the TelePhysio app. In addition, the study investigated the concurrent validity, between-sessions, and inter-rater reliability of a second tele-assessment approach using video analysis. Methods: Fifteen participants (nfemales = 6) were assessed in our laboratory (session 1) and at their home (session 2). We assessed maximum voluntary active hip flexion in supine and hip internal and external rotation, in both prone and sitting positions. TelePhysio and video analysis were validated against the laboratory’s 3-dimensional motion capture system in session 1, and evaluated for between-sessions reliability in session 2. Video analysis inter-rater reliability was assessed by comparing the analysis of two raters in session 2. Results: The TelePhysio app demonstrated high concurrent validity against the 3D motion capture system (ICCs 0.63–0.83) for all hip movements in all positions, with the exception of hip internal rotation in prone (ICC = 0.48, p = 0.99). The video analysis demonstrated almost perfect concurrent validity against the 3D motion capture system (ICCs 0.85–0.94) for all hip movements in all positions, with the exception of hip internal rotation in prone (ICC = 0.44, p = 0.01). The TelePhysio and video analysis demonstrated good between-sessions reliability for hip external rotation and hip flexion, ICC 0.64 and 0.62, respectively. The between-sessions reliability of hip internal and external rotation for both TelePhysio and video analysis was fair (ICCs 0.36–0.63). Inter-rater reliability ICCs for the video analysis were 0.59 for hip flexion and 0.87–0.95 for the hip rotation range. Conclusions: Both tele-assessment approaches, using either a smartphone application or video analysis, demonstrate good to excellent concurrent validity, and moderate to substantial between-sessions reliability in measuring hip rotation and flexion range of motion, but less in internal hip rotation in the prone position. Thus, it is recommended that the seated position be used when assessing hip internal rotation. The use of a smartphone to remotely assess hip range of motion is an appropriate, effective, and low-cost alternative to the face-to-face assessments. This method provides a simple, cost effective, and accessible patient assessment tool with no additional cost. This study validates the use of smartphone technology as a tele-assessment tool for remote hip range of motion assessment. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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8 pages, 1533 KiB

Open AccessCommunication

Assessment of Socket Pressure during Walking in Rapid Fit Prosthetic Sockets

by Kazuhiko Sasaki, Gary Guerra, Win Lei Phyu, Sirarat Chaisumritchoke, Prawina Sutdet and Sirintip Kaewtip

Sensors 2022, 22(14), 5224; https://doi.org/10.3390/s22145224 - 13 Jul 2022

Cited by 3 | Viewed by 2323

Abstract

(1) Background: A sustainable casting system that combines the use of a polystyrene bag, a prosthetic liner and a vacuum system was developed to reduce fabrication time while maintaining comfort for the trans-tibial prosthesis user. (2) Methods: Eight prosthetists (28.7 ± 8.25 years old) fit ten trans-tibial prosthesis wearers (46 ± 12.4 years old) with two types of total surface bearing (TSB) prostheses; a polystyrene bead (PS) prosthesis and a plaster of paris (POP) prosthesis. Duration of casting and combined mean peak pressure was measured at six locations on the residual limb using Force Sensing Resistors (FSR). A pressure uniformity score (%) was determined. Socket Comfort Scale (SCS) was also measured. (3) Results: Duration of casting for the POP method was 64.8 ± 9.53 min and 7.8 ± 2 min for the PS method, (p = 0.006). Pressure uniformity in the POP prosthesis was 79.3 ± 6.54 and 81.7 ± 5.83 in the PS prosthesis (p = 0.027). SCS in both prosthesis types were equivalent. (4) Conclusion: A rapid fit PS prosthesis was developed, with significantly shorter duration than the traditional POP method. Socket pressure uniformity was confirmed and improved in the PS method. Socket comfort was equal between the two prothesis types. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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12 pages, 2508 KiB

Open AccessArticle

Inertia Sensors for Measuring Spasticity of the Ankle Plantarflexors Using the Modified Tardieu Scale—A Proof of Concept Study

by Megan Banky, Gavin Williams, Rebecca Davey and Oren Tirosh

Sensors 2022, 22(14), 5151; https://doi.org/10.3390/s22145151 - 9 Jul 2022

Cited by 3 | Viewed by 1947

Abstract

Ankle spasticity is clinically assessed using goniometry to measure the angle of muscle reaction during the Modified Tardieu Scale (MTS). The precision of the goniometric method is questionable as the measured angle may not represent when the spastic muscle reaction occurred. This work proposes a method to accurately determine the angle of muscle reaction during the MTS assessment by measuring the maximum angular velocity and the corresponding ankle joint angle, using two affordable inertial sensors. Initially we identified the association between muscle onset and peak joint angular velocity using surface electromyography and an inertial sensor. The maximum foot angular velocity occurred 0.049 and 0.032 s following the spastic muscle reaction for Gastrocnemius and Soleus, respectively. Next, we explored the use of two affordable inertial sensors to identify the angle of muscle reaction using the peak ankle angular velocity. The angle of muscle reaction and the maximum dorsiflexion angle were significantly different for both Gastrocnemius and Soleus MTS tests (p = 0.028 and p = 0.009, respectively), indicating that the system is able to accurately detect a spastic muscle response before the end of the movement. This work successfully demonstrates how wearable technology can be used in a clinical setting to identify the onset of muscle spasticity and proposes a more accurate method that clinicians can use to measure the angle of muscle reaction during the MTS assessment. Furthermore, the proposed method may provide an opportunity to monitor the degree of spasticity where the direct help of experienced therapists is inaccessible, e.g., in rural or remote areas. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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13 pages, 1948 KiB

Open AccessArticle

Validation of 3-Space Wireless Inertial Measurement Units Using an Industrial Robot

by Jaime Hislop, Mats Isaksson, John McCormick and Chris Hensman

Sensors 2021, 21(20), 6858; https://doi.org/10.3390/s21206858 - 15 Oct 2021

Cited by 9 | Viewed by 2197

Abstract

Inertial Measurement Units (IMUs) are beneficial for motion tracking as, in contrast to most optical motion capture systems, IMU systems do not require a dedicated lab. However, IMUs are affected by electromagnetic noise and may exhibit drift over time; it is therefore common practice to compare their performance to another system of high accuracy before use. The 3-Space IMUs have only been validated in two previous studies with limited testing protocols. This study utilized an IRB 2600 industrial robot to evaluate the performance of the IMUs for the three sensor fusion methods provided in the 3-Space software. Testing consisted of programmed motion sequences including 360° rotations and linear translations of 800 mm in opposite directions for each axis at three different velocities, as well as static trials. The magnetometer was disabled to assess the accuracy of the IMUs in an environment containing electromagnetic noise. The Root-Mean-Square Error (RMSE) of the sensor orientation ranged between 0.2° and 12.5° across trials; average drift was 0.4°. The performance of the three filters was determined to be comparable. This study demonstrates that the 3-Space sensors may be utilized in an environment containing metal or electromagnetic noise with a RMSE below 10° in most cases. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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16 pages, 2026 KiB

Open AccessSystematic Review

Recent State of Wearable IMU Sensors Use in People Living with Spasticity: A Systematic Review

by Yehuda Weizman, Oren Tirosh, Franz Konstantin Fuss, Adin Ming Tan and Erich Rutz

Sensors 2022, 22(5), 1791; https://doi.org/10.3390/s22051791 - 24 Feb 2022

Cited by 16 | Viewed by 3332

Abstract

Spasticity is a disabling characteristic of neurological disorders, described by a velocity-dependent increase in muscle tone during passive stretch. During the last few years, many studies have been carried out to assess spasticity using wearable IMU (inertial measurements unit) sensors. This review aims to provide an updated framework of the current research on IMUs wearable sensors in people living with spasticity in recent studies published between 2017 and 2021. A total of 322 articles were screened, then finally 10 articles were selected. Results show the lack of homogenization of study procedures and missing apparatus information in some studies. Still, most studies performed adequately on measures of reporting and found that IMUs wearable data was successful in their respective purposes and goals. As IMUs estimate translational and rotational body motions, we believe there is a strong potential for these applications to estimate velocity-dependent exaggeration of stretch reflexes and spasticity-related characteristics in spasticity. This review also proposes new directions of research that should be challenged by larger study groups and could be of interest to both researchers as well as clinicians. The use of IMUs to evaluate spasticity is a promising avenue to provide an objective measurement as compared to non-instrumented traditional assessments. Full article

(This article belongs to the Special Issue Wearable Sensors for Human Movement)

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