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Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport

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

Deadline for manuscript submissions: closed (10 May 2024) | Viewed by 21354

Special Issue Editors


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Guest Editor
Faculty of Information, Media and Electrical Engineering, Institute of Media and Imaging Technology, TH Köln, Köln, Germany
Interests: motion capture; sensor technologies; digital health; machine learning; computer animation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Orthopedics and Trauma Surgery, University Hospital of Bonn, 53127 Bonn, Germany
Interests: orthopedic surgery; hand surgery; nerve computer interface; motion tracking; xR

Special Issue Information

Dear Colleagues,

There have been great advances in the capture and analysis of human motion in the past two decades: On the one hand, we have seen a rapid development in sensor technology, where smaller sensors are able to capture motion data in high levels of detail at high frame rates. These sensors allow for the capturing of motion parameters over long time periods, collecting data in so-called “out of the lab” scenarios, with high comfort for the user and professional. Based on such data, it is possible to analyze patients’ behaviour in an everyday environment. Even in lab situations, new sensors make it possible to capture details of motion that have not been possible to record in the past.

On the other hand, new techniques for the analysis of large amounts of data have emerged in the last years. Based on machine learning, deep learning, and artificial intelligence approaches, we are now able to gain insights from the recorded data, at much higher levels, leading to a deeper understanding of the underlying motion patterns.

The combination of new hardware and software technology leads to emerging applications and use cases in a broad range of areas. In this Special Issue we want to focus on developments and applications of the abovementioned sensor and software technologies in the field of medicine, rehabilitation, and sport.

Dr. Björn Krüger
Dr. Kristian Welle
Guest Editors

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Keywords

  • wearable technology
  • motion analysis
  • machine learning
  • Rehabilitation
  • medical devices
  • digital health

Published Papers (12 papers)

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Research

12 pages, 2240 KiB  
Article
Comparing the Drop Vertical Jump Tracking Performance of the Azure Kinect to the Kinect V2
by Patrik Abdelnour, Kevin Y. Zhao, Athanasios Babouras, Jason Philip Aaron Hiro Corban, Nicolaos Karatzas, Thomas Fevens and Paul Andre Martineau
Sensors 2024, 24(12), 3814; https://doi.org/10.3390/s24123814 - 13 Jun 2024
Viewed by 112
Abstract
Traditional motion analysis systems are impractical for widespread screening of non-contact anterior cruciate ligament (ACL) injury risk. The Kinect V2 has been identified as a portable and reliable alternative but was replaced by the Azure Kinect. We hypothesize that the Azure Kinect will [...] Read more.
Traditional motion analysis systems are impractical for widespread screening of non-contact anterior cruciate ligament (ACL) injury risk. The Kinect V2 has been identified as a portable and reliable alternative but was replaced by the Azure Kinect. We hypothesize that the Azure Kinect will assess drop vertical jump (DVJ) parameters associated with ACL injury risk with similar accuracy to its predecessor, the Kinect V2. Sixty-nine participants performed DVJs while being recorded by both the Azure Kinect and the Kinect V2 simultaneously. Our software analyzed the data to identify initial coronal, peak coronal, and peak sagittal knee angles. Agreement between the two systems was evaluated using the intraclass correlation coefficient (ICC). There was poor agreement between the Azure Kinect and the Kinect V2 for initial and peak coronal angles (ICC values ranging from 0.135 to 0.446), and moderate agreement for peak sagittal angles (ICC = 0.608, 0.655 for left and right knees, respectively). At this point in time, the Azure Kinect system is not a reliable successor to the Kinect V2 system for assessment of initial coronal, peak coronal, and peak sagittal angles during a DVJ, despite demonstrating superior tracking of continuous knee angles. Alternative motion analysis systems should be explored. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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13 pages, 31824 KiB  
Article
A Method to Track 3D Knee Kinematics by Multi-Channel 3D-Tracked A-Mode Ultrasound
by Kenan Niu, Victor Sluiter, Bangyu Lan, Jasper Homminga, André Sprengers and Nico Verdonschot
Sensors 2024, 24(8), 2439; https://doi.org/10.3390/s24082439 - 11 Apr 2024
Viewed by 517
Abstract
This paper introduces a method for measuring 3D tibiofemoral kinematics using a multi-channel A-mode ultrasound system under dynamic conditions. The proposed system consists of a multi-channel A-mode ultrasound system integrated with a conventional motion capture system (i.e., optical tracking system). This approach allows [...] Read more.
This paper introduces a method for measuring 3D tibiofemoral kinematics using a multi-channel A-mode ultrasound system under dynamic conditions. The proposed system consists of a multi-channel A-mode ultrasound system integrated with a conventional motion capture system (i.e., optical tracking system). This approach allows for the non-invasive and non-radiative quantification of the tibiofemoral joint’s six degrees of freedom (DOF). We demonstrated the feasibility and accuracy of this method in the cadaveric experiment. The knee joint’s motions were mimicked by manually manipulating the leg through multiple motion cycles from flexion to extension. To measure it, six custom ultrasound holders, equipped with a total of 30 A-mode ultrasound transducers and 18 optical markers, were mounted on various anatomical regions of the lower extremity of the specimen. During experiments, 3D-tracked intra-cortical bone pins were inserted into the femur and tibia to measure the ground truth of tibiofemoral kinematics. The results were compared with the tibiofemoral kinematics derived from the proposed ultrasound system. The results showed an average rotational error of 1.51 ± 1.13° and a translational error of 3.14 ± 1.72 mm for the ultrasound-derived kinematics, compared to the ground truth. In conclusion, this multi-channel A-mode ultrasound system demonstrated a great potential of effectively measuring tibiofemoral kinematics during dynamic motions. Its improved accuracy, nature of non-invasiveness, and lack of radiation exposure make this method a promising alternative to incorporate into gait analysis and prosthetic kinematic measurements later. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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13 pages, 1934 KiB  
Article
Variability between Different Hand-Held Dynamometers for Measuring Muscle Strength
by William Du, Kayla M. D. Cornett, Gabrielle A. Donlevy, Joshua Burns and Marnee J. McKay
Sensors 2024, 24(6), 1861; https://doi.org/10.3390/s24061861 - 14 Mar 2024
Viewed by 1121
Abstract
Muscle strength is routinely measured in patients with neuromuscular disorders by hand-held dynamometry incorporating a wireless load cell to evaluate disease severity and therapeutic efficacy, with magnitude of effect often based on normative reference values. While several hand-held dynamometers exist, their interchangeability is [...] Read more.
Muscle strength is routinely measured in patients with neuromuscular disorders by hand-held dynamometry incorporating a wireless load cell to evaluate disease severity and therapeutic efficacy, with magnitude of effect often based on normative reference values. While several hand-held dynamometers exist, their interchangeability is unknown which limits the utility of normative data. We investigated the variability between six commercially available dynamometers for measuring the isometric muscle strength of four muscle groups in thirty healthy individuals. Following electro-mechanical sensor calibration against knowns loads, Citec, Nicholas, MicroFET2, and Commander dynamometers were used to assess the strength of ankle dorsiflexors, hip internal rotators, and shoulder external rotators. Citec, Jamar Plus, and Baseline Hydraulic dynamometers were used to capture hand grip strength. Variability between dynamometers was represented as percent differences and statistical significance was calculated with one-way repeated measures ANOVA. Percent differences between dynamometers ranged from 0.2% to 16%. No significant differences were recorded between the Citec, Nicholas, and MicroFET2 dynamometers (p > 0.05). Citec grip strength measures differed to the Jamar Plus and Baseline Hydraulic dynamometers (p < 0.01). However, when controlling for grip circumference, they were comparable (p > 0.05). Several hand-held dynamometers can be used interchangeably to measure upper and lower limb strength, thereby maximising the use of normative reference values. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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28 pages, 2605 KiB  
Article
An Effective and Efficient Approach for 3D Recovery of Human Motion Capture Data
by Hashim Yasin, Saba Ghani and Björn Krüger
Sensors 2023, 23(7), 3664; https://doi.org/10.3390/s23073664 - 31 Mar 2023
Viewed by 2046
Abstract
In this work, we propose a novel data-driven approach to recover missing or corrupted motion capture data, either in the form of 3D skeleton joints or 3D marker trajectories. We construct a knowledge-base that contains prior existing knowledge, which helps us to make [...] Read more.
In this work, we propose a novel data-driven approach to recover missing or corrupted motion capture data, either in the form of 3D skeleton joints or 3D marker trajectories. We construct a knowledge-base that contains prior existing knowledge, which helps us to make it possible to infer missing or corrupted information of the motion capture data. We then build a kd-tree in parallel fashion on the GPU for fast search and retrieval of this already available knowledge in the form of nearest neighbors from the knowledge-base efficiently. We exploit the concept of histograms to organize the data and use an off-the-shelf radix sort algorithm to sort the keys within a single processor of GPU. We query the motion missing joints or markers, and as a result, we fetch a fixed number of nearest neighbors for the given input query motion. We employ an objective function with multiple error terms that substantially recover 3D joints or marker trajectories in parallel on the GPU. We perform comprehensive experiments to evaluate our approach quantitatively and qualitatively on publicly available motion capture datasets, namely CMU and HDM05. From the results, it is observed that the recovery of boxing, jumptwist, run, martial arts, salsa, and acrobatic motion sequences works best, while the recovery of motion sequences of kicking and jumping results in slightly larger errors. However, on average, our approach executes outstanding results. Generally, our approach outperforms all the competing state-of-the-art methods in the most test cases with different action sequences and executes reliable results with minimal errors and without any user interaction. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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12 pages, 1279 KiB  
Article
A Novel Classification of Coronal Plane Knee Joint Instability Using Nine-Axis Inertial Measurement Units in Patients with Medial Knee Osteoarthritis
by Hiroaki Tsukamoto, Kimio Saito, Hidetomo Saito, Hiroaki Kijima, Manabu Akagawa, Akira Komatsu, Takehiro Iwami and Naohisa Miyakoshi
Sensors 2023, 23(5), 2797; https://doi.org/10.3390/s23052797 - 3 Mar 2023
Cited by 2 | Viewed by 1780
Abstract
The purpose of this study was to propose a novel classification of varus thrust based on gait analysis with inertial motion sensor units (IMUs) in patients with medial knee osteoarthritis (MKOA). We investigated thigh and shank acceleration using a nine-axis IMU in 69 [...] Read more.
The purpose of this study was to propose a novel classification of varus thrust based on gait analysis with inertial motion sensor units (IMUs) in patients with medial knee osteoarthritis (MKOA). We investigated thigh and shank acceleration using a nine-axis IMU in 69 knees with MKOA and 24 (control) knees. We classified varus thrust into four phenotypes according to the relative medial–lateral acceleration vector patterns of the thigh and shank segments: pattern A (thigh medial, shank medial), pattern B (medial, lateral), pattern C (lateral, medial), and pattern D (lateral, lateral). Quantitative varus thrust was calculated using an extended Kalman filter-based algorithm. We compared the differences between our proposed IMU classification and the Kellgren–Lawrence (KL) grades for quantitative varus thrust and visible varus thrust. Most of the varus thrust was not visually perceptible in early-stage OA. In advanced MKOA, increased proportions of patterns C and D with lateral thigh acceleration were observed. Quantitative varus thrust was significantly increased stepwise from patterns A to D. This novel IMU classification has better clinical utility due to its ability to detect subtle kinematic changes that cannot be captured with conventional motion analysis even in the early stage of MKOA. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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20 pages, 8308 KiB  
Article
3D Autonomous Surgeon’s Hand Movement Assessment Using a Cascaded Fuzzy Supervisor in Multi-Thread Video Processing
by Fatemeh Rashidi Fathabadi, Janos L. Grantner, Saad A. Shebrain and Ikhlas Abdel-Qader
Sensors 2023, 23(5), 2623; https://doi.org/10.3390/s23052623 - 27 Feb 2023
Cited by 6 | Viewed by 1476
Abstract
The purpose of the Fundamentals of Laparoscopic Surgery (FLS) training is to develop laparoscopic surgery skills by using simulation experiences. Several advanced training methods based on simulation have been created to enable training in a non-patient environment. Laparoscopic box trainers—cheap, portable devices—have been [...] Read more.
The purpose of the Fundamentals of Laparoscopic Surgery (FLS) training is to develop laparoscopic surgery skills by using simulation experiences. Several advanced training methods based on simulation have been created to enable training in a non-patient environment. Laparoscopic box trainers—cheap, portable devices—have been deployed for a while to offer training opportunities, competence evaluations, and performance reviews. However, the trainees must be under the supervision of medical experts who can evaluate their abilities, which is an expensive and time-consuming operation. Thus, a high level of surgical skill, determined by assessment, is necessary to prevent any intraoperative issues and malfunctions during a real laparoscopic procedure and during human intervention. To guarantee that the use of laparoscopic surgical training methods results in surgical skill improvement, it is necessary to measure and assess surgeons’ skills during tests. We used our intelligent box-trainer system (IBTS) as a platform for skill training. The main aim of this study was to monitor the surgeon’s hands’ movement within a predefined field of interest. To evaluate the surgeons’ hands’ movement in 3D space, an autonomous evaluation system using two cameras and multi-thread video processing is proposed. This method works by detecting laparoscopic instruments and using a cascaded fuzzy logic assessment system. It is composed of two fuzzy logic systems executing in parallel. The first level assesses the left and right-hand movements simultaneously. Its outputs are cascaded by the final fuzzy logic assessment at the second level. This algorithm is completely autonomous and removes the need for any human monitoring or intervention. The experimental work included nine physicians (surgeons and residents) from the surgery and obstetrics/gynecology (OB/GYN) residency programs at WMU Homer Stryker MD School of Medicine (WMed) with different levels of laparoscopic skills and experience. They were recruited to participate in the peg-transfer task. The participants’ performances were assessed, and the videos were recorded throughout the exercises. The results were delivered autonomously about 10 s after the experiments were concluded. In the future, we plan to increase the computing power of the IBTS to achieve real-time performance assessment. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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11 pages, 1052 KiB  
Article
Efficacy of Proprioceptive Training on Plantar Pressure and Jump Performance in Volleyball Players: A Proof-of-Principle Study
by Nicola Marotta, Lucrezia Moggio, Dario Calafiore, Emanuele Prestifilippo, Riccardo Spanó, Anna Tasselli, Vera Drago Ferrante, Marco Invernizzi, Alessandro de Sire and Antonio Ammendolia
Sensors 2023, 23(4), 1906; https://doi.org/10.3390/s23041906 - 8 Feb 2023
Cited by 3 | Viewed by 2327
Abstract
Volleyball players are often subject to micro-traumatisms of the heel fat pad and ankle injuries. Recently, mat-based proprioceptive training has assumed a key role in recovery from these disorders. Therefore, this proof-of-principle study aimed to assess the efficacy of proprioceptive mat training on [...] Read more.
Volleyball players are often subject to micro-traumatisms of the heel fat pad and ankle injuries. Recently, mat-based proprioceptive training has assumed a key role in recovery from these disorders. Therefore, this proof-of-principle study aimed to assess the efficacy of proprioceptive mat training on plantar pressures and athletic performance in volleyball players. The participants included adult semi-professional volleyball players allocated into two groups: an experimental group, with mat-based proprioceptive and balance training, and a control group, with a sham protocol. For the outcome, we evaluated the barefoot plantar pressure, performing an analysis on a baropodometric resistive platform. The countermovement jump and squat jump were measured using an inertial measurement unit. Nineteen subjects were included in the two groups: the active proprioceptive group (n = 10) or the control group (n = 9). The results show a more uniform redistribution of loads with pressure hindfoot relief in the experimental group compared to the control group (p = 0.021, RBC = 0.67). Moreover, we observed a significant increase in peak landing force and high concentric power development in the experimental group compared to the controls. Focused proprioceptive management provided hindfoot load attenuation by stimulating higher peaks of concentric force in the experimental group compared to the sham group. Even though the study included a small sample, the results obtained in this proof-of-principle study suggest a positive role of proprioceptive stimulation in the inter-seasonal scenario for volleyball players to improve their jump performance and reduce the micro-traumatisms of the heel fat pad and the ankle injury rate. However, further studies performed on larger samples are needed to confirm these preliminary results. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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14 pages, 5372 KiB  
Article
Revealing the Mutual Information between Body-Worn Sensors and Metabolic Cost in Running
by Tobias Baumgartner, Stefanie Klatt and Lars Donath
Sensors 2023, 23(4), 1756; https://doi.org/10.3390/s23041756 - 4 Feb 2023
Viewed by 1600
Abstract
Running power is a popular measure to gauge objective intensity. It has recently been shown, though, that foot-worn sensors alone cannot reflect variations in the exerted energy that stems from changes in the running economy. In order to support long-term improvement in running, [...] Read more.
Running power is a popular measure to gauge objective intensity. It has recently been shown, though, that foot-worn sensors alone cannot reflect variations in the exerted energy that stems from changes in the running economy. In order to support long-term improvement in running, these changes need to be taken into account. We propose leveraging the presence of two additional sensors worn by the most ambitious recreational runners for improved measurement: a watch and a heart rate chest strap. Using these accelerometers, which are already present and distributed over the athlete’s body, carries more information about metabolic demand than a single foot-worn sensor. In this work, we demonstrate the mutual information between acceleration data and the metabolic demand of running by leveraging the information bottleneck of a constrained convolutional neural network. We perform lab measurements on 29 ambitious recreational runners (age = 28 ± 7 years, weekly running distance = 50 ± 25 km, V˙O2max = 60.3 ± 7.4 mL · min−1·kg−1). We show that information about the metabolic demand of running is contained in kinetic data. Additionally, we prove that the combination of three sensors (foot, torso, and lower arm) carries significantly more information than a single foot-worn sensor. We advocate for the development of running power systems that incorporate the sensors in watches and chest straps to improve the validity of running power and, thereby, long-term training planning. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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13 pages, 2449 KiB  
Article
A Wireless Rowing Measurement System for Improving the Rowing Performance of Athletes
by Richard Hohmuth, Daniel Schwensow, Hagen Malberg and Martin Schmidt
Sensors 2023, 23(3), 1060; https://doi.org/10.3390/s23031060 - 17 Jan 2023
Cited by 4 | Viewed by 2840
Abstract
The rowing technique is a key factor in the overall rowing performance. Nowadays the athletes’ performance is so advanced that even small differences in technique can have an impact on sport competitions. To further improve the athletes’ performance, individualized rowing is necessary. This [...] Read more.
The rowing technique is a key factor in the overall rowing performance. Nowadays the athletes’ performance is so advanced that even small differences in technique can have an impact on sport competitions. To further improve the athletes’ performance, individualized rowing is necessary. This can be achieved by intelligent measurement technology that provides direct feedback. To address this issue, we developed a novel wireless rowing measurement system (WiRMS) that acquires rowing movement and measures muscle activity using electromyography (EMG). Our measurement system is able to measure several parameters simultaneously: the rowing forces, the pressure distribution on the scull, the oar angles, the seat displacement and the boat acceleration. WiRMS was evaluated in a proof-of-concept study with seven experienced athletes performing a training on water. Evaluation results showed that WiRMS is able to assess the rower’s performance by recording the rower’s movement and force applied to the scull. We found significant correlations (p < 0.001) between stroke rate and drive-to-recovery ratio. By incorporating EMG data, a precise temporal assignment of the activated muscles and their contribution to the rowing motion was possible. Furthermore, we were able to show that the rower applies the force to the scull mainly with the index and middle fingers. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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13 pages, 4836 KiB  
Article
Development of a Wearable Haptic Glove Presenting Haptic Sensation by Electrical Stimulation
by Dongbo Zhou, Wataru Hayakawa, Yoshikazu Nakajima and Kotaro Tadano
Sensors 2023, 23(1), 431; https://doi.org/10.3390/s23010431 - 30 Dec 2022
Cited by 2 | Viewed by 2093
Abstract
Most haptic devices generate haptic sensation using mechanical actuators. However, the workload and limited workspace handicap the operator from operating freely. Electrical stimulation is an alternative approach to generate haptic sensations without using mechanical actuators. The light weight of the electrodes adhering to [...] Read more.
Most haptic devices generate haptic sensation using mechanical actuators. However, the workload and limited workspace handicap the operator from operating freely. Electrical stimulation is an alternative approach to generate haptic sensations without using mechanical actuators. The light weight of the electrodes adhering to the body brings no limitations to free motion. Because a real haptic sensation consists of feelings from several areas, mounting the electrodes to several different body areas can make the sensations more realistic. However, simultaneously stimulating multiple electrodes may result in “noise” sensations. Moreover, the operators may feel tingling because of unstable stimulus signals when using the dry electrodes to help develop an easily mounted haptic device using electrical stimulation. In this study, we first determine the appropriate stimulation areas and stimulus signals to generate a real touch sensation on the forearm. Then, we propose a circuit design guideline for generating stable electrical stimulus signals using a voltage divider resistor. Finally, based on the aforementioned results, we develop a wearable haptic glove prototype. This haptic glove allows the user to experience the haptic sensations of touching objects with five different degrees of stiffness. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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16 pages, 6113 KiB  
Article
Design of a Multi-Sensor System for Exploring the Relation between Finger Spasticity and Voluntary Movement in Patients with Stroke
by Bor-Shing Lin, I-Jung Lee, Pei-Chi Hsiao, Shu-Yu Yang, Chen-Yu Chen, Si-Huei Lee, Yu-Fang Huang, Mao-Hsu Yen and Yu Hen Hu
Sensors 2022, 22(19), 7212; https://doi.org/10.3390/s22197212 - 23 Sep 2022
Cited by 3 | Viewed by 2061
Abstract
A novel wearable multi-sensor data glove system is developed to explore the relation between finger spasticity and voluntary movement in patients with stroke. Many stroke patients suffer from finger spasticity, which is detrimental to their manual dexterity. Diagnosing and assessing the degrees of [...] Read more.
A novel wearable multi-sensor data glove system is developed to explore the relation between finger spasticity and voluntary movement in patients with stroke. Many stroke patients suffer from finger spasticity, which is detrimental to their manual dexterity. Diagnosing and assessing the degrees of spasticity require neurological testing performed by trained professionals to estimate finger spasticity scores via the modified Ashworth scale (MAS). The proposed system offers an objective, quantitative solution to assess the finger spasticity of patients with stroke and complements the manual neurological test. In this work, the hardware and software components of this system are described. By requiring patients to perform five designated tasks, biomechanical measurements including linear and angular speed, acceleration, and pressure at every finger joint and upper limb are recorded, making up more than 1000 features for each task. We conducted a preliminary clinical test with 14 subjects using this system. Statistical analysis is performed on the acquired measurements to identify a small subset of features that are most likely to discriminate a healthy patient from patients suffering from finger spasticity. This encouraging result validates the feasibility of this proposed system to quantitatively and objectively assess finger spasticity. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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17 pages, 3131 KiB  
Article
Providing Real-Time Wearable Feedback to Increase Hand Use after Stroke: A Randomized, Controlled Trial
by Diogo Schwerz de Lucena, Justin B. Rowe, Shusuke Okita, Vicky Chan, Steven C. Cramer and David J. Reinkensmeyer
Sensors 2022, 22(18), 6938; https://doi.org/10.3390/s22186938 - 14 Sep 2022
Cited by 5 | Viewed by 1934
Abstract
After stroke, many people substantially reduce use of their impaired hand in daily life, even if they retain even a moderate level of functional hand ability. Here, we tested whether providing real-time, wearable feedback on the number of achieved hand movements, along with [...] Read more.
After stroke, many people substantially reduce use of their impaired hand in daily life, even if they retain even a moderate level of functional hand ability. Here, we tested whether providing real-time, wearable feedback on the number of achieved hand movements, along with a daily goal, can help people increase hand use intensity. Twenty participants with chronic stroke wore the Manumeter, a novel magnetic wristwatch/ring system that counts finger and wrist movements. We randomized them to wear the device for three weeks with (feedback group) or without (control group) real-time hand count feedback and a daily goal. Participants in the control group used the device as a wristwatch, but it still counted hand movements. We found that the feedback group wore the Manumeter significantly longer (11.2 ± 1.3 h/day) compared to the control group (10.1 ± 1.1 h/day). The feedback group also significantly increased their hand counts over time (p = 0.012, slope = 9.0 hand counts/hour per day, which amounted to ~2000 additional counts per day by study end), while the control group did not (p-value = 0.059; slope = 4.87 hand counts/hour per day). There were no significant differences between groups in any clinical measures of hand movement ability that we measured before and after the feedback period, although several of these measures improved over time. Finally, we confirmed that the previously reported threshold relationship between hand functional capacity and daily use was stable over three weeks, even in the presence of feedback, and established the minimal detectable change for hand count intensity, which is about 30% of average daily intensity. These results suggest that disuse of the hand after stroke is temporarily modifiable with wearable feedback, but do not support that a 3-week intervention of wearable hand count feedback provides enduring therapeutic gains. Full article
(This article belongs to the Special Issue Sensor-Based Motion Analysis in Medicine, Rehabilitation and Sport)
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