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Human hands and fingers have been widely studied in different fields, such as animation, biomechanics, ergonomics, rehabilitation, medicine, and robotics. However, since the hands are a highly complex part of the human body capable of developing precise tasks, replicating human hand mechanisms remains challenging and, thus, continues to be an active area. This study focuses on a bioinspired mechanically equivalent finger model. A parametric model was proposed based on the typical architecture of a human finger, allowing adaptation to different anthropometries. A forward kinematic model assesses each phalanx's range of motion (ROM) during flexion-extension and abduction-adduction. A CAD modeling technique based on fused filament fabrication (FFF) is used for easy fabrication, requiring no assembly. The resulting model achieves the desired ROM, offering a simple solution for hand modeling. This bioinspired model aids in training hand exoskeleton robots, accurately mimicking human finger mechanics for various applications, including rehabilitation and prosthetics. This model helps understand complex hand mechanisms and holds potential for robotics and related fields.

Introduction

Many researchers have built pedobarography measurement systems [1]. Pedobarography, the study of forces interacting between the plantar surface of the feet and a supporting surface, can be used in many applications. Examples are analysis of gait and posture in for example orthotics design and monitoring of rehabilitation. Force sensing resistors (FSR) measure approximately the ground reaction force which is the force acting on the foot from the insole. Low sensor height, high linearity and good durability are three important sensor properties. FSRs are down to 0.2mm thick but can be non-linear and they can break easily if implemented wrongly. How can the FSRs be implemented in insoles and calibrated to overcome these sensor type shortcomings?

Implementation

Discrete FSRs are often placed at the heel, inside and outside of the metatarsal pad and the big toe pad. It is vital to protect the boundary of the active sensor area. If the boundary is exposed to too much mechanical strain it will rapidly break down. This is because the upper and lower layers of the sensor get short-circuited. First the sensor will show intermittent maximum values and later stop working at all. One solution is to remove insole material right under the sensor boundary to relieve it from mechanical strain [2].

Calibration

The FSR manufacturers recommend using at least four different loads for the calibration and be aware that static load makes the sensor drift over time. It is important to choose a similar calibration procedure as the application it will be used for, e.g. dynamic calibration if the application is measurement while walking. A load cell should be used for calibrating the FSR. Linear or exponential regression are not recommended. Three or fourth power polynomials have shown to produce acceptable errors [3].

Discussion

FSRs have two less than ideal properties regarding linearity and durability. The lifetime of the sensor can be increased by taking special care of not exposing the active sensor area boundary to mechnical stress. Calibration should be done dynamically if the application is e.g. measurment while walking. Three power, or higher, polynomials are recomended for the regression.

References

• [1] N. Hegde, et al., A Comparative Review of Footwear-Based Wearable Systems. Electronics 5(3), (2016).
• [2] P. A. R. Hellström, Wireless Wearable Measurement System Based on Pedobarography for Monitoring of Health. Lic. Thes., (2016).
• [3] J. M. Brimacombe, et al., Effect of calibration method on Tekscan sensor accuracy. J. Biomech. Eng. 131(3), (2009).

Human motion analysis provides several important applications. Examples are fall risk assessment, sports biomechanics, physical activity monitoring and rehabilitation. This work in progress paper proposes an intelligent wireless body area network system for motion and gait symmetry analysis. A Bluetooth network with accelerometers, gyroscopes and in-shoe force sensing resistors gathers data and sends it to a web server after intelligent pre-processing and filtering. The system is flexible and adaptable for different use cases including combinations of gait analysis, gait symmetry and pressure measurements between foot and shoe.

Earlier work has shown that the IngVaL pedobarography system can estimate walking speed during indoor walking using only three forefoot sensors. The aim of this study was to examine if monitoring of walking speed using data from these three forefoot sensors is affected of the weight a person carries, if the person performs a walk in a set speed on the treadmill. Shoe insoles with force sensing resistors were connected to an electronic unit for signal conditioning and sampling and then the data was sent via Bluetooth to a tablet. Fifteen test persons walked five times each carrying five different weights on the treadmill at 1 m/s. The force-time integrals for the sum of the three forefoot sensors were calculated. This study shows that the force-time integrals for the three forefoot sensors shows a linear relationship with the carried weight as long as the person is not fatigued.

Personal health monitoring is advantageous in heavy work environments to reduce the risk of wear and tear and acute injuries. The study of forces between the plantar surface of the foot and a supporting structure, pedobarography, is a  promising candidate for monitoring carried weight during walk. The aim of this study was to evaluate the cost effective pedobarography measurement system, IngVaL. Two aspects are evaluated, namely, how well IngVaL can monitor carried weight during walk and if the novel implementation increased the durability. Fifteen test persons made five treadmill walks with a carried weight of 10, 20, 0, 15, and 5 kg. The equipoise analysis method was used. The Root Mean Square Error (RMSE) for estimation of the carried weight was 13.8 kg. A study with the earlier version of the measurement system had a RMSE of 23.3 kg. The earlier system, as well as commercial systems using this kind of sensors, have problems with sensor durability. The new sensor implementation, where the active sensor area boundary was no longer affected by mechanical stress, resulted in no broken sensors. This study shows an increased performance of carried weight estimation compared with earlier work, together with an improved sensor durability.

The total amount of lifted weights and lift frequency are moderate to strong risk factors for lower back pain. Measurement of carried weight is thereby of interest. The aim of this paper is to (1) present three novel analyses methods for estimation of weight during walk and (2) to describe the design process of the cost-effective research system IngVaL based on pedobarography. The paper will also (3) present the durability of the sensors. Motivations for choices in the system design are given for hardware, selection of sensor type, sensor implementation and calibration of sensors. To measure weight during walk with IngVaL, fifteen test persons made five walks each with a pseudo-random added extra weight. Three analyses methods were tested, for estimation of weight while walking, resulting in Root Mean Square Errors of 11.3 kg, 7.1 kg and 6.1 kg respectively. The durability of the sensors were tested in an outdoors walking condition. It can be concluded that the IngVaL system shows good durability and that weight during walk is possible to measure with simple analyses methods.

Heavy working conditions, as well as sedentary behaviour, are risk factors for health. There is a lack of wearable measurement systems for monitoring carried loads while walking. Pedobarography, the study of force fields acting between the plantar surface of the foot and a supporting surface, is supposed to be useable for estimating carried loads. Purpose. The aim of this paper is to present a novel method for selecting appropriate measurement samples for weight estimation of carried load during walk and a wearable system, based on pedobarography, consisting of commercial off the shelf components. The main idea is to choose samples when half of the total weight is on the forward sensors and the other half is on the heel sensor “equipoise” in one foot while the other foot not touches the ground. Methods. The system consists of insoles with force sensing resistors, data acquisition with IOIO-OTG and analysis in Excel. Each subject was weighed on an electronic floor scale. Three walks were performed on level ground. The first walk without any added load and then with two increases of carried load. Equipoise was defined as having half the weight distributed on the heel and the other half over the metatarsal pad. An equipoise value of 0.5 represents equilibrium regarding the weight distribution on one foot, with the other foot in the air. Samples were chosen in the equipoise region of 0.5±0.1 and then the average of the samples collected during one minute estimated the total weight. Results. The system can detect increases in carried loads but has a tendency to overestimate them. The estimated value was always larger with increased weight but the system was not always linear. The average overestimation error was 16.7 kg. Discussion. This study shows that this type of wearable system is usable for estimating carried load during walk after calibration of the system to the body weight force distribution on the sensors. There is still need for future development to obtain real-time analysis and direct feedback. A smaller and lighter measurement system is also desirable. Conclusion. This study shows that the novel method, equipoise, is usable for selecting appropriate measurement samples for weight estimation of carried load during walk. This study also shows that the wearable system, consisting of commercial off the shelf components, can be used for these measurements. However, there is a tendency to overestimate the loads.

Objectives

Walking speed is an important component of movement and is a predictor of health in the elderly. Pedobarography, the study of forces acting between the plantar surface of the foot and a supporting surface, is an approach to estimating walking speed even when no global positioning system signal is available. The developed portable system, Identifying Velocity and Load (IngVaL), is a cost effective alternative to commercially available pedobarography systems because it only uses three force sensing resistors. In this study, the IngVaL system was evaluated. The three variables investigated in this study were the sensor durability, the proportion of analyzable steps, and the linearity between the system output and the walking speed.

Methods

Data was collected from 40 participants, each of whom performed five walks at five different self-paced walking speeds. The linearity between the walking speed and step frequency measured with R2 values was compared for the walking speed obtained ‘A’ only using amplitude data from the force sensors, ‘B’ that obtained only using the step frequency, and ‘C’ that obtained by combining amplitude data for each of the 40 test participants.

Results

Improvement of the wireless data transmission increased the percentage of analyzable steps from 83.1% measured with a prototype to 96.6% for IngVaL. The linearity comparison showed that the methods A, B, and C were accurate for 2, 15, and 23 participants, respectively.

Conclusions

Increased sensor durability and a higher percentage of analyzed steps indicates that IngVaL is an improvement over the prototype system. The combined strategy of amplitude and step frequency was confirmed as the most accurate method.

The aim of this pilot study was to investigate the possibility to find a correlation between the output from a portable pedobarography system and the walking intensity expressed as walking speed. The system uses shoe insoles with force sensing resistors and wireless transmission of the data via Bluetooth. The force-time integral, at the toe-off phase of the step, for the force sensors in the forward part of the right foot was used to measure impulse data for 10 subjects performing walks in three different walking speeds. This data was then corrected by multiplication with the step frequency. This pilot study indicates that the portable pedobarography system output shows a linear relationship with the walking intensity expressed as walking speed on an individual level.

Introduction

When lifting a package or during strength training, right posture of the back is important to avoid back pain. Different sensor solutions to measure posture of the back are presented in research articles and patents. The aim of this study was to investigate the possibility of using Lumo Lift as a device of giving feedback of good posture when lifting weights.

Method

Lumo Lift (Lumo Body Tech, Inc, USA) is an activity tracker aimed to for example guide the carrier to good posture. The small device is attached to the clothes using a magnetic clasp. It is calibrated to the user's good posture and vibrates when the posture is inaccurate. In this study the angle, in which the Lumo Lift is allowed to tilt before the device vibrates, was investigated. The device was placed at the top of a ruler and calibrated in upright position. Thereafter the ruler was tilted and the angle when the equipment vibrated was noted. Two different speeds of the tilts were performed. One speed simulating the normal speed of an inaccurate tilting torso when lifting weights. And one slow speed. Two Lumo Lifts were tilted 20 times forward and backwards, respectively.

Result

In normal speed the measured angle was between 6 and 25 degrees, when tilted forward, except two times when one of the devices gave no vibration during the whole tilt of 90 degrees. When tilted backwards the angle was between 8 and 32 degrees. During slow tilt the angle varied from 5 to 13 degrees forward and 4 to 13 degrees backwards.

Discussion and conclusion

Angle tilted before vibration is too large in normal tilting speed. This study indicates that Lumo Lift is not suitable of giving posture feedback during lifting in daily life.

Health care costs have increased over the last decades due to an ageing population. Therefore, research in personal health monitoring (PHM) has increased in response to this. PHM has advantages such as mobility (monitoring of health at work or at home), early detection of health problems enabling preventive health measures and a reduction of health care cost. Human motion analysis, using for example pedobarography (PBG), is an important subcategory of PHM. PBG is used to study the force fields acting between the plantar surface of the foot and a supporting surface. Gait and posture analysis, prosthetics evaluation and monitoring of recovery from injury or disease are examples of PBG applications. Portable PBG can be performed using force sensing resistors built into the insole inside the shoe.

 In accordance with this, the research aim for this thesis is to design, build and evaluate a wireless wearable measurement system based on PBG for monitoring of walk related parameters. Monitoring of carried weight and walking speed were chosen as the applications for validation of the system. Motivations for choosing these applications are that there is a lack of a wearable system for monitoring of weight while walking and a possible combination with accelerometers to improve the estimation of walking speed. Both walking speed and weight are important factors for estimating energy expenditure. A portable system, that estimates weight while walking, enables monitoring of heavy working conditions.

The main research contributions include design of a PBG measurement system with a sensor implementation resulting in good sensor durability, several novel methods for weight estimation during walk and a novel method for analysing walking intensity and relating it to walking speed. The research results show that the new PBG system, in combination with the novel analysing methods, are suitable for use in wearable systems for monitoring of health related walk parameters.

Health care costs have increased over the last decades due to an ageing population. Therefore, research in personal health monitoring (PHM) has increased in response to this. PHM has advantages such as mobility (monitoring of health at work or at home), early detection of health problems enabling preventive health measures and a reduction of health care cost. Human motion analysis, using for example inertial measurement units and pedobarography, is an important subcategory of PHM. Pedobarography (PBG) is the study of pressure fields acting between the plantar surface of the foot and a supporting surface. Gait and posture analysis, prosthetics evaluation and monitoring of recovery from injury or disease are examples of PBG applications. Portable PBG can be performed using force sensing resistors built into the insole inside the shoe.

In accordance with this, the research goal for this licentiate thesis is to design, build and evaluate a wireless wearable measurement system based on pedobarography for monitoring of health. In order to fulfil the objectives of the research, literature studies were done and problems with existing in-shoe system solutions were identified. Thus, it was found that further opportunities existed for new designs of PBG systems which take these problems into account. Cross-sectional test case studies were used for validation. The research area is multidisciplinary and encompasses biomedical measurements, electronics and computer science.

The main research contributions include design and implementation of a PBG measurement system consisting of commercial off the shelf components, a novel method for selecting measurement samples for weight estimation of carried load during walk, and a novel method for analysing walking intensity using force-time integrals at the toe-off phase of the step. The research results suggest that the new PBG system, in combination with the two novel analysing methods, are suitable for use in wearable systems for monitoring of health. Personal health measurements are done to help decision making related to health. Thus, the future work will strive towards designing different decision support systems.

Hand rehabilitation has been widely studied since it affects the life quality and independence of those affected. Hand impairment can be caused by several conditions, among them strokes and other cerebrovascular accidents, affecting the capabilities of those who survive them in performing the activities of daily living (ADL). Rehabilitation seeks to restore the ability of a person to perform these crucial ADL. There is a current trend in using robotic rehabilitation and other industry 4.0 tools since it can provide a safe, intensive, and task-oriented at a relatively low cost, which can be combined with other technologies such as virtual and augmented reality, BCI, haptics, and others. Moreover, it can provide accessibility in the face of current panoramas such as COVID-19. Hand exoskeleton robots are one of the most extended robotic devices for rehabilitation. However, a design adapted to the patient's needs is necessary to achieve their capability fully and succeed in rehabilitation. One of the main challenges is that several considerations and parameters affect these devices' design and the broad approaches that can be followed. This brief review aims to understand and empathize as a source of inspiration during the design process of hand exoskeleton robots for rehabilitation.