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Fulltext Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification

Sikandar T, Rabbi MF, Ghazali KH, Altwijri O, Alqahtani M, Almijalli M, et al.

Sensors (Basel), 2021 Apr 17;21(8).
PMID: 33920617 DOI: 10.3390/s21082836

Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environments, respectively. Additionally, the proposed ratio-based body measurement data are independent of body-worn garments and not susceptible to changes in the distance between the walking individual and camera. As a simple but efficient technique, the proposed walking speed classification has great potential to be employed in clinics and aged care homes.

Matched MeSH terms: Walking; Walking Speed*
Information-based analysis of the relation between human muscle reaction and walking path

Kamal SM, Dawi NBM, Sim S, Tee R, Nathan V, Aghasian E, et al.

Technol Health Care, 2020;28(6):675-684.
PMID: 32200366 DOI: 10.3233/THC-192034

BACKGROUND: Walking is one of the important actions of the human body. For this purpose, the human brain communicates with leg muscles through the nervous system. Based on the walking path, leg muscles act differently. Therefore, there should be a relation between the activity of leg muscles and the path of movement.
OBJECTIVE: In order to address this issue, we analyzed how leg muscle activity is related to the variations of the path of movement.
METHOD: Since the electromyography (EMG) signal is a feature of muscle activity and the movement path has complex structures, we used entropy analysis in order to link their structures. The Shannon entropy of EMG signal and walking path are computed to relate their information content.
RESULTS: Based on the obtained results, walking on a path with greater information content causes greater information content in the EMG signal which is supported by statistical analysis results. This allowed us to analyze the relation between muscle activity and walking path.
CONCLUSION: The method of analysis employed in this research can be applied to investigate the relation between brain or heart reactions and walking path.

Matched MeSH terms: Walking*
Decoding of the relationship between human brain activity and walking paths

Kamal SM, Sim S, Tee R, Nathan V, Aghasian E, Namazi H

Technol Health Care, 2020;28(4):381-390.
PMID: 31796717 DOI: 10.3233/THC-191965

BACKGROUND: The human brain controls all actions of the body. Walking is one of the most important actions that deals with the movement of the body. In fact, the brain controls and regulates human walking based on different conditions. One of the conditions that affects human walking is the complexity of path of movement. Therefore, the brain activity should change when a person walks on a path with different complexities.
OBJECTIVE: In this research we benefit from fractal analysis to study the effect of complexity of path of movement on the complexity of human brain reaction.
METHODS: For this purpose we calculate the fractal dimension of the electroencephalography (EEG) signal when subjects walk on different paths with different fractal dimensions (complexity).
RESULTS: The results of the analysis show that the complexity of brain activity increases with the increment of complexity of path of movement.
CONCLUSION: The method of analysis employed in this research can also be employed to analyse the reaction of the human heart and respiration when subjects move on paths with different complexities.

Matched MeSH terms: Walking*
Order error in the calculation of continuous relative phase

Mehdizadeh S, Glazier PS

J Biomech, 2018 05 17;73:243-248.
PMID: 29628131 DOI: 10.1016/j.jbiomech.2018.03.032

The aims of this study were to demonstrate "order error" in the calculation of continuous relative phase (CRP) and to suggest two alternative methods-(i) constructing phase-plane portraits by plotting position over velocity; and (ii), the Hilbert transform-to rectify it. Order error is the change of CRP order between two degrees of freedom (e.g., body segments) when using the conventional method of constructing phase-plane portraits (i.e., velocity over position). Both sinusoidal and non-sinusoidal simulated signals as well as signals from human movement kinematics were used to investigate order error and the performance of the two alternative methods. Both methods have been shown to lead to correct results for simulated sinusoidal and non-sinusoidal signals. For human movement data, however, the Hilbert transform is superior for calculating CRP.

Matched MeSH terms: Walking/physiology*
Information-based decoding of the coupling among human brain activity and movement paths

Kamal SM, Dawi NM, Namazi H

Technol Health Care, 2021;29(6):1109-1118.
PMID: 33749623 DOI: 10.3233/THC-202744

BACKGROUND: Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements.
OBJECTIVE: This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view.
METHODS: We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents.
RESULTS: According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.

Matched MeSH terms: Walking*
Effect of simulated sensorimotor noise on kinematic variability and stability of a biped walking model

Mehdizadeh S, Glazier PS

Comput Methods Biomech Biomed Engin, 2021 Aug;24(10):1097-1103.
PMID: 33426927 DOI: 10.1080/10255842.2020.1867852

Whether higher variability in older adults' walking is an indication of increased instability has been challenged recently. We performed a computer simulation to investigate the effect of sensorimotor noise on the kinematic variability and stability in a biped walking model. Stochastic differential equations of the system with additive Gaussian white noise was constructed and solved. Sensorimotor noise mainly resulted in higher kinematic variability but its influence on gait stability is minimal. This implies that kinematic variability evident in walking gaits of older adults could be the result of internal sensorimotor noise and not an indication of instability.

Matched MeSH terms: Walking*
Fulltext Minimum number of inertial measurement units needed to identify significant variations in walk patterns of overweight individuals walking on irregular surfaces

Sikandar T, Rabbi MF, Ghazali KH, Altwijri O, Almijalli M, Ahamed NU

Sci Rep, 2023 Sep 27;13(1):16177.
PMID: 37758958 DOI: 10.1038/s41598-023-43428-9

Gait data collection from overweight individuals walking on irregular surfaces is a challenging task that can be addressed using inertial measurement unit (IMU) sensors. However, it is unclear how many IMUs are needed, particularly when body attachment locations are not standardized. In this study, we analysed data collected from six body locations, including the torso, upper and lower limbs, to determine which locations exhibit significant variation across different real-world irregular surfaces. We then used deep learning method to verify whether the IMU data recorded from the identified body locations could classify walk patterns across the surfaces. Our results revealed two combinations of body locations, including the thigh and shank (i.e., the left and right shank, and the right thigh and right shank), from which IMU data should be collected to accurately classify walking patterns over real-world irregular surfaces (with classification accuracies of 97.24 and 95.87%, respectively). Our findings suggest that the identified numbers and locations of IMUs could potentially reduce the amount of data recorded and processed to develop a fall prevention system for overweight individuals.

Matched MeSH terms: Walking*
Fulltext The Influence of Virtual Forest Walk on Physiological and Psychological Responses

Alyan E, Combe T, Awang Rambli DR, Sulaiman S, Merienne F, Muhaiyuddin NDM

Int J Environ Res Public Health, 2021 Oct 29;18(21).
PMID: 34769937 DOI: 10.3390/ijerph182111420

The authors of this paper sought to investigate the impact of virtual forest therapy based on realistic versus dreamlike environments on reducing stress levels. Today, people are facing an increase in stress levels in everyday life, which may be due to personal life, work environment, or urban area expansion. Previous studies have reported that urban environments demand more attention and mental workload than natural environments. However, evidence for the effects of natural environments as virtual forest therapy on stress levels has not yet been fully explored. In this study, a total of 20 healthy participants completed a letter-detection test to increase their stress level and were then randomly assigned to two different virtual environments representing realistic and dreamlike graphics. The participants' stress levels were assessed using two physiological methods that measured heart rate and skin conductance levels and one psychological method through the Profile of Mood States (POMS) questionnaire. These indicators were analyzed using a sample t-test and a one-way analysis of variance. The results showed that virtual forest environments could have positive stress-relieving effects. However, realistic graphics were more efficient in reducing stress. These findings contribute to growing forest therapy concepts and provide new directions for future forest therapy research.

Matched MeSH terms: Walking*
Random walk behaviour of malaysia share return in different economic circumstance

Muhammad Fadhil Marsani, Ani Shabri

MATEMATIKA, 2019;35(3):297-308.
MyJurnal

This journal renders the random walk behaviour of the Malaysian daily share return, through tests of efficient market hypothesis (EMH) based on three different financial periods, namely growth, financial crisis, and recovery period. This review also covers the behaviour of extreme return for weekly and monthly series generated from Block maxima-minima method. Autocorrelation Function test (ACF) and Ljung-Box test had been employed to measure average correlation between observations, while Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), Kwiatkowski Phillips Schmidt Shin (KPSS) test had been used to scan the unit root and the stationarity. Multiple variance ratio tests had also been conducted to examine the random walk behaviour. Serial correlation test indicated that the movement of daily return during the financial crisis period was weak-form efficiency. The unit root and stationary tests suggested that each daily series was stationary, but trend stationary for extreme cases. Variance ratio tests indicated that the return during the recovery period was weak-form inefficiency due to the short lag autocorrelation in series.

Matched MeSH terms: Walking
Is monetary variable a determinant in the ringgit-dollar exchange rates model?: a cointegration approach

Gharleghi B, Abu Hassan Shaari Md Nor

Sains Malaysiana, 2012;41:1163-1169.

The main aim of this paper was to validate the relative price monetary model (RPMM) of exchange rate determination for the Malaysian exchange rate (RM/USD) using monthly data set from 1986-2010. The Johansen multivariate cointegration test and vector error correction model were employed. Because the time period under consideration includes the South
East Asian financial crisis, the analysis is done using two time periods; the full time period as well as the period after the crisis. Two interesting results were observed from this empirical exercise. First, there is a long-run relationship between exchange rate and the selected macro variables only for the period after the crisis. Second, the forecasting performance of monetary approach based on the error correction model outperformed the Random Walk model.

Matched MeSH terms: Walking
Evaluating the difference in walk patterns among normal-weight and overweight/obese individuals in real-world surfaces using statistical analysis and deep learning methods with inertial measurement unit data

Sikandar T, Rabbi MF, Ghazali KH, Altwijri O, Almijalli M, Ahamed NU

Phys Eng Sci Med, 2022 Dec;45(4):1289-1300.
PMID: 36352317 DOI: 10.1007/s13246-022-01195-3

Unusual walk patterns may increase individuals' risks of falling. Anthropometric features of the human body, such as the body mass index (BMI), influences the walk patterns of individuals. In addition to the BMI, uneven walking surfaces may cause variations in the usual walk patterns of an individual that will potentially increase the individual's risk of falling. The objective of this study was to statistically evaluate the variations in the walk patterns of individuals belonging to two BMI groups across a wide range of walking surfaces and to investigate whether a deep learning method could classify the BMI-specific walk patterns with similar variations. Data collected by wearable inertial measurement unit (IMU) sensors attached to individuals with two different BMI were collected while walking on real-world surfaces. In addition to traditional statistical analysis tools, an advanced deep learning-based neural network was used to evaluate and classify the BMI-specific walk patterns. The walk patterns of overweight/obese individuals showed a greater correlation with the corresponding walking surfaces than the normal-weight population. The results were supported by the deep learning method, which was able to classify the walk patterns of overweight/obese (94.8 ± 4.5%) individuals more accurately than those of normal-weight (59.4 ± 23.7%) individuals. The results suggest that application of the deep learning method is more suitable for recognizing the walk patterns of overweight/obese population than those of normal-weight individuals. The findings from the study will potentially inform healthcare applications, including artificial intelligence-based fall assessment systems for minimizing the risk of fall-related incidents among overweight and obese individuals.

Matched MeSH terms: Walking
Investigation of EMG parameter for transtibial prosthetic user with flexion and extension of the knee and normal walking gait: A preliminary study

Sobh KNM, Abd Razak NA, Abu Osman NA

Proc Inst Mech Eng H, 2021 Apr;235(4):419-427.
PMID: 33517847 DOI: 10.1177/0954411920985753

Electromyography signal has been used widely as input for prosthetic's leg movements. C-Leg, for example, is among the prosthetics devices that use electromyography as the main input. The main challenge facing the industrial party is the position of the electromyography sensor as it is fixed inside the socket. The study aims to investigate the best positional parameter of electromyography for transtibial prosthetic users for the device to be effective in multiple movement activities and compare with normal human muscle's activities. DELSYS Trigno wireless electromyography instrument was used in this study to achieve this aim. Ten non-amputee subjects and two transtibial amputees were involved in this study. The surface electromyography signals were recorded from two anterior and posterior below the knee muscles and above the knee muscles, respectively: tibial anterior and gastrocnemius lateral head as well as rectus femoris and biceps femoris during two activities (flexion and extension of knee joint and gait cycle for normal walking). The result during flexion and extension activities for gastrocnemius lateral head and biceps femoris muscles was found to be more useful for the control subjects, while the tibial anterior and also gastrocnemius lateral head are more active for amputee subjects. Also, during normal walking activity for biceps femoris and gastrocnemius lateral head, it was more useful for the control subjects, while for transtibial amputee subject-1, the rectus femoris was the highest signal of the average normal walking activity (0.0001 V) compared to biceps femoris (0.00007 V), as for transtibial amputee subject-2, the biceps femoris was the highest signals of the average normal walking activity (0.0001 V) compared to rectus femoris (0.00004 V). So, it is difficult to rely entirely on the static positioning of the electromyography sensor within the socket as there is a possibility of the sensor to contact with inactive muscle, which will be a gap in the control, leading to a decrease in the functional efficiency of the powered prostheses.

Matched MeSH terms: Walking*
Fulltext Muscles Affecting Minimum Toe Clearance

Perera CK, Gopalai AA, Ahmad SA, Gouwanda D

Front Public Health, 2021;9:612064.
PMID: 34136448 DOI: 10.3389/fpubh.2021.612064

The aim of this study was to investigate how the anterior and posterior muscles in the shank (Tibialis Anterior, Gastrocnemius Lateralis and Medialis), influence the level of minimum toe clearance (MTC). With aging, MTC deteriorates thus, greatly increasing the probability of falling or tripping. This could result in injury or even death. For this study, muscle activity retention taping (MART) was used on young adults, which is an accepted method of simulating a poor MTC-found in elderly gait. The subject's muscle activation was measured using surface electromyography (SEMG), and the kinematic parameters (MTC, knee and ankle joint angles) were measured using an optical motion capture system. Our results indicate that MART produces significant reductions in MTC (P < α), knee flexion (P < α) and ankle dorsiflexion (P < α), as expected. However, the muscle activity increased significantly, contrary to the expected result (elderly individuals should have lower muscle activity). This was due to the subject's muscle conditions (healthy and strong), hence the muscles worked harder to counteract the external restriction. Yet, the significant change in muscle activity (due to MART) proves that the shank muscles do play an important role in determining the level of MTC. The Tibialis Anterior had the highest overall muscle activation, making it the primary muscle active during the swing phase. With aging, the shank muscles (specifically the Tibialis Anterior) would weaken and stiffen, coupled with a reduced joint range of motion. Thus, ankle-drop would increase-leading to a reduction in MTC.

Matched MeSH terms: Walking*
Fulltext Gait Analysis in Patients with Wide Resection and Endoprosthesis Replacement Around the Knee

Singh VA, Heng CW, Yasin NF

Indian J Orthop, 2018 2 9;52(1):65-72.
PMID: 29416172 DOI: 10.4103/ortho.IJOrtho_188_17

Background: Limb salvage surgery with endoprosthesis for bone tumor around the knee is reported to have good functional and oncological outcomes. However, the functional assessment using musculoskeletal tumor society (MSTS) and Toronto extremity scoring system remains subjective. We performed gait analysis as an objective assessment of their functional outcome.
Materials and Methods: Gait analysis was performed in 20 patients with endoprosthesis replacement around the knee. The temporal parameters assessed during gait analysis were walking velocity, stride length, duration of stance, and goniometry of the knee. These parameters were compared with the functional outcome score of the MSTS.
Results: The mean free-paced walking velocity was 0.91 m/s (normal is 1.33 m/s), which was 68% lower than normal gait. The stride length and stance phase were shorter for the affected limb compared to normal (P < 0.05). However, the gait was symmetrical with no difference in stride length (P = 0.148), velocity (P = 0.918), knee flexion (P = 0.465), and knee extension (P = 0.321) between the affected and unaffected limbs. Sixteen patients demonstrated stiff knee gait, two had a flexed knee gait, and only two patients had normal gait during the stance phase. The mean MSTS score was 21. There was significant correlation between overall MSTS scores (P = 0.023), function (P = 0.039), and walking scores (P = 0.007).
Conclusion: Limb salvage surgery with endoprosthesis reconstruction around the knee gives good functional outcome, both objectively and subjectively, as evidenced by the symmetrical gait pattern and significant correlation with MSTS score. Despite decreased walking velocity, stride length, and stance phase of the operated limb, the patient still has a symmetrical gait.

Matched MeSH terms: Walking; Walking Speed
Alcohol-impaired Walking in 16 Countries: A Theory-Based Investigation

Oviedo-Trespalacios O, Çelik AK, Marti-Belda A, Włodarczyk A, Demant D, Nguyen-Phuoc DQ, et al.

Accid Anal Prev, 2021 Sep;159:106212.
PMID: 34098429 DOI: 10.1016/j.aap.2021.106212

Alcohol is a global risk factor for road trauma. Although drink driving has received most of the scholarly attention, there is growing evidence of the risks of alcohol-impaired walking. Alcohol-impaired pedestrians are over-represented in fatal crashes compared to non-impaired pedestrians. Additionally, empirical evidence shows that alcohol intoxication impairs road-crossing judgements. Besides some limited early research, much is unknown about the global prevalence and determinants of alcohol-impaired walking. Understanding alcohol-impaired walking will support health promotion initiatives and injury prevention. The present investigation has three aims: (1) compare the prevalence of alcohol-impaired walking across countries; (2) identify international groups of pedestrians based on psychosocial factors (i.e., Theory of Planned Behaviour (TPB) and perceptions of risk); and (3) investigate how segments of pedestrians form their intention for alcohol-impaired walking using the extended TPB (i.e. subjective norm, attitudes, perceived control, and perceived risk). A cross-sectional design was applied. The target behaviour question was "have you been a pedestrian when your thinking or physical ability (balance/strength) is affected by alcohol?" to ensure comparability across countries. Cluster analysis based on the extended TPB was used to identify groups of countries. Finally, regressions were used to predict pedestrians' intentions per group. A total of 6,166 respondents (Age M(SD) = 29.4 (14.2); Males = 39.2%) completed the questionnaire, ranging from 12.6% from Russia to 2.2% from Finland. The proportion of participants who reported never engaging in alcohol-impaired walking in the last three months ranged from 30.1% (Spain) to 83.1% (Turkey). Four groups of countries were identified: group-1 (Czech Republic, Spain, and Australia), group-2 (Russia and Finland), group-3 (Japan), and group-4 (final ten countries including Colombia, China, and Romania). Pedestrian intentions to engage in alcohol- impaired walking are predicted by perceptions of risk and TPB-psychosocial factors in group-1 and group-4. Favourable TPB-beliefs and low perceived risk increased alcohol-impaired walking intentions. Conversely, subjective norms were not significant in group-2 and only perceived risk predicted intention in group-3. The willingness of pedestrians to walk when alcohol-impaired differs significantly across the countries in this study. Perceived risk was the only common predictor among the 16 countries.

Matched MeSH terms: Walking*
Fulltext A Systematic Approach to the Design and Characterization of A Smart Insole for Detecting Vertical Ground Reaction Force (vGRF) in Gait Analysis

Tahir AM, Chowdhury MEH, Khandakar A, Al-Hamouz S, Abdalla M, Awadallah S, et al.

Sensors (Basel), 2020 Feb 11;20(4).
PMID: 32053914 DOI: 10.3390/s20040957

Gait analysis is a systematic study of human locomotion, which can be utilized in variousapplications, such as rehabilitation, clinical diagnostics and sports activities. The various limitationssuch as cost, non-portability, long setup time, post-processing time etc., of the current gait analysistechniques have made them unfeasible for individual use. This led to an increase in research interestin developing smart insoles where wearable sensors can be employed to detect vertical groundreaction forces (vGRF) and other gait variables. Smart insoles are flexible, portable and comfortablefor gait analysis, and can monitor plantar pressure frequently through embedded sensors thatconvert the applied pressure to an electrical signal that can be displayed and analyzed further.Several research teams are still working to improve the insoles' features such as size, sensitivity ofinsoles sensors, durability, and the intelligence of insoles to monitor and control subjects' gait bydetecting various complications providing recommendation to enhance walking performance. Eventhough systematic sensor calibration approaches have been followed by different teams to calibrateinsoles' sensor, expensive calibration devices were used for calibration such as universal testingmachines or infrared motion capture cameras equipped in motion analysis labs. This paper providesa systematic design and characterization procedure for three different pressure sensors: forcesensitiveresistors (FSRs), ceramic piezoelectric sensors, and flexible piezoelectric sensors that canbe used for detecting vGRF using a smart insole. A simple calibration method based on a load cellis presented as an alternative to the expensive calibration techniques. In addition, to evaluate theperformance of the different sensors as a component for the smart insole, the acquired vGRF fromdifferent insoles were used to compare them. The results showed that the FSR is the most effectivesensor among the three sensors for smart insole applications, whereas the piezoelectric sensors canbe utilized in detecting the start and end of the gait cycle. This study will be useful for any researchgroup in replicating the design of a customized smart insole for gait analysis.

Matched MeSH terms: Walking*
Effect of noise and filtering on largest Lyapunov exponent of time series associated with human walking

Mehdizadeh S, Sanjari MA

J Biomech, 2017 11 07;64:236-239.
PMID: 28958634 DOI: 10.1016/j.jbiomech.2017.09.009

This study aimed to determine the effect of added noise, filtering and time series length on the largest Lyapunov exponent (LyE) value calculated for time series obtained from a passive dynamic walker. The simplest passive dynamic walker model comprising of two massless legs connected by a frictionless hinge joint at the hip was adopted to generate walking time series. The generated time series was used to construct a state space with the embedding dimension of 3 and time delay of 100 samples. The LyE was calculated as the exponential rate of divergence of neighboring trajectories of the state space using Rosenstein's algorithm. To determine the effect of noise on LyE values, seven levels of Gaussian white noise (SNR=55-25dB with 5dB steps) were added to the time series. In addition, the filtering was performed using a range of cutoff frequencies from 3Hz to 19Hz with 2Hz steps. The LyE was calculated for both noise-free and noisy time series with different lengths of 6, 50, 100 and 150 strides. Results demonstrated a high percent error in the presence of noise for LyE. Therefore, these observations suggest that Rosenstein's algorithm might not perform well in the presence of added experimental noise. Furthermore, findings indicated that at least 50 walking strides are required to calculate LyE to account for the effect of noise. Finally, observations support that a conservative filtering of the time series with a high cutoff frequency might be more appropriate prior to calculating LyE.

Matched MeSH terms: Walking/physiology*
Challenges and opportunity in mobility among older adults - key determinant identification

Maresova P, Krejcar O, Maskuriy R, Bakar NAA, Selamat A, Truhlarova Z, et al.

BMC Geriatr, 2023 Jul 21;23(1):447.
PMID: 37474928 DOI: 10.1186/s12877-023-04106-7

BACKGROUND: Attention is focused on the health and physical fitness of older adults due to their increasing age. Maintaining physical abilities, including safe walking and movement, significantly contributes to the perception of health in old age. One of the early signs of declining fitness in older adults is limited mobility. Approximately one third of 70-year-olds and most 80-year-olds report restrictions on mobility in their apartments and immediate surroundings. Restriction or loss of mobility is a complex multifactorial process, which makes older adults prone to falls, injuries, and hospitalizations and worsens their quality of life while increasing overall mortality.
OBJECTIVE: The objective of the study is to identify the factors that have had a significant impact on mobility in recent years and currently, and to identify gaps in our understanding of these factors. The study aims to highlight areas where further research is needed and where new and effective solutions are required.
METHODS: The PRISMA methodology was used to conduct a scoping review in the Scopus and Web of Science databases. Papers published from 2007 to 2021 were searched in November 2021. Of these, 52 papers were selected from the initial 788 outputs for the final analysis.
RESULTS: The final selected papers were analyzed, and the key determinants were found to be environmental, physical, cognitive, and psychosocial, which confirms the findings of previous studies. One new determinant is technological. New and effective solutions lie in understanding the interactions between different determinants of mobility, addressing environmental factors, and exploring opportunities in the context of emerging technologies, such as the integration of smart home technologies, design of accessible and age-friendly public spaces, development of policies and regulations, and exploration of innovative financing models to support the integration of assistive technologies into the lives of seniors.
CONCLUSION: For an effective and comprehensive solution to support senior mobility, the determinants cannot be solved separately. Physical, cognitive, psychosocial, and technological determinants can often be perceived as the cause/motivation for mobility. Further research on these determinants can help to arrive at solutions for environmental determinants, which, in turn, will help improve mobility. Future studies should investigate financial aspects, especially since many technological solutions are expensive and not commonly available, which limits their use.

Matched MeSH terms: Walking*
Fulltext Quantification of Gait Stability During Incline and Decline Walking: The Responses of Required Coefficient of Friction and Dynamic Postural Index

Abdul Yamin NAA, Basaruddin KS, Abu Bakar S, Salleh AF, Mat Som MH, Yazid H, et al.

J Healthc Eng, 2022;2022:7716821.
PMID: 36275397 DOI: 10.1155/2022/7716821

This study aims to investigate the gait stability response during incline and decline walking for various surface inclination angles in terms of the required coefficient of friction (RCOF), postural stability index (PSI), and center of pressure (COP)-center of mass (COM) distance. A customized platform with different surface inclinations (0°, 5°, 7.5°, and 10°) was designed. Twenty-three male volunteers participated by walking on an inclined platform for each inclination. The process was then repeated for declined platform as well. Qualysis motion capture system was used to capture and collect the trajectories motion of ten reflective markers that attached to the subjects before being exported to a visual three-dimensional (3D) software and executed in Matlab to obtain the RCOF, PSI, as well as dynamic PSI (DPSI) and COP-COM distance parameters. According to the result for incline walking, during initial contact, the RCOF was not affected to inclination. However, it was affected during peak ground reaction force (GRF) starting at 7.5° towards 10° for both walking conditions. The most affected PSI was found at anterior-posterior PSI (APSI) even as low as 5° inclination during both incline and decline walking. On the other hand, DPSI was not affected during both walking conditions. Furthermore, COP-COM distance was most affected during decline walking in anterior-posterior direction. The findings of this research indicate that in order to decrease the risk of falling and manage the inclination demand, a suitable walking strategy and improved safety measures should be applied during slope walking, particularly for decline and anterior-posterior orientations. This study also provides additional understanding on the best incline walking technique for secure and practical incline locomotion.

Matched MeSH terms: Walking/physiology
Fulltext Multisensor automatic balancing model for DARwIn-OP on uneven terrain

Muhamad Khuzaifah Ismail, Meng Cheng Lau, Mohammad Faidzul Nasrudin, Haslina Arsha

Pertanika Journal of Science & Technology, 2017;25(106):181-188.
MyJurnal

The walking of a humanoid robot needs to be robust enough in order to maintain balance in a dynamic environment especially on uneven terrain. A walking model based on multi-sensor is proposed for a Robotis DARwIn-OP robot named as Leman. Two force sensitive resistor (FSRs) on both feet equipped to Leman to estimate the zero moment point (ZMP) alongside with accelerometer and gyrosensor embedded in the body for body state estimation. The results show that the FSRs can successfully detect the unbalanced walking event if the protuberance exists on the floor surface and the accelerometer and gyrosensor (Inertial Measurement Unit, IMU) data are recorded to tune the balancing parameter in the model.

Matched MeSH terms: Walking

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