A biomechanical perspective on walking in patients with peripheral artery disease.

The most common symptom of peripheral artery disease (PAD) is intermittent claudication, which consists of debilitating leg pain during walking. In clinical settings, the presence of PAD is often noninvasively evaluated using the ankle-brachial index and imaging of the arterial supply. Furthermore, various questionnaires and functional tests are commonly used to measure the severity and negative effect of PAD on quality of life. However, these evaluations only provide information on vascular insufficiency and severity of the disease, but not regarding the complex mechanisms underlying walking impairments in patients with PAD. Biomechanical analyses using motion capture and ground reaction force measurements can provide insight into the underlying mechanisms to walking impairments in PAD. This review analyzes the application of biomechanics tools to identify gait impairments and their clinical implications on rehabilitation of patients with PAD. A total of 18 published journal articles focused on gait biomechanics in patients with PAD were studied. This narriative review shows that the gait of patients with PAD is impaired from the first steps that a patient takes and deteriorates further after the onset of claudication leg pain. These results point toward impaired muscle function across the ankle, knee, and hip joints during walking. Gait analysis helps understand the mechanisms operating in PAD and could also facilitate earlier diagnosis, better treatment, and slower progression of PAD.

Trunk Velocity Changes in Response to Physical Perturbations Are Potential Indicators of Gait Stability.

Response to challenging situations is important to avoid falls, especially after medial perturbations, which require active control. There is a lack of evidence on the relationship between the trunk's motion in response to perturbations and gait stability. Eighteen healthy adults walked on a treadmill at three speeds while receiving perturbations of three magnitudes. Medial perturbations were applied by translating the walking platform to the right at left heel contact. Trunk velocity changes in response to the perturbation were calculated and divided into the initial and the recovery phases. Gait stability after a perturbation was assessed using the margin of stability (MOS) at the first heel contact, MOS mean, and standard deviation for the first five strides after the perturbation onset. Faster speed and smaller perturbations led to a lower deviation of trunk velocity from the steady state, which can be interpreted as an improvement in response to the perturbation. Recovery was quicker after small perturbations. The MOS mean was associated with the trunk's motion in response to perturbations during the initial phase. Increasing walking speed may increase resistance to perturbations, while increasing the magnitude of perturbation leads to greater trunk motions. MOS is a useful marker of resistance to perturbations.

Machine Learning-Based Peripheral Artery Disease Identification Using Laboratory-Based Gait Data.

Peripheral artery disease (PAD) manifests from atherosclerosis, which limits blood flow to the legs and causes changes in muscle structure and function, and in gait performance. PAD is underdiagnosed, which delays treatment and worsens clinical outcomes. To overcome this challenge, the purpose of this study is to develop machine learning (ML) models that distinguish individuals with and without PAD. This is the first step to using ML to identify those with PAD risk early. We built ML models based on previously acquired overground walking biomechanics data from patients with PAD and healthy controls. Gait signatures were characterized using ankle, knee, and hip joint angles, torques, and powers, as well as ground reaction forces (GRF). ML was able to classify those with and without PAD using Neural Networks or Random Forest algorithms with 89% accuracy (0.64 Matthew's Correlation Coefficient) using all laboratory-based gait variables. Moreover, models using only GRF variables provided up to 87% accuracy (0.64 Matthew's Correlation Coefficient). These results indicate that ML models can classify those with and without PAD using gait signatures with acceptable performance. Results also show that an ML gait signature model that uses GRF features delivers the most informative data for PAD classification.

Patient Compliance With Wearing Lower Limb Assistive Devices: A Scoping Review.

OBJECTIVE: The aim of this scoping review was to identify information on compliance with wearing orthoses and other supportive devices, to discuss the barriers to adherence, and to suggest strategies for improvement based on these findings. METHODS: Online databases of PubMed, Web of Science, and the Cochrane Library were searched for articles about patients' compliance with regard to lower limb assistive devices. In addition, a methodological quality control process was conducted. Studies were included if in the English language and related to compliance and adherence to the lower limb assistive device. Exclusion was based on first reading the abstract and then the full manuscript confirming content was not related to orthotic devices and compliance. RESULTS: Twelve studies were included. The data revealed between 6% and 80% of patients were not using a prescribed device. Barriers to the use of the orthotic device included medical, functional, device properties and lack of proper fit. Strategies for improved compliance included better communication between patient and clinician, patient education, and improved comfort and device esthetics. CONCLUSIONS: Individualized orthotic adjustments, rehabilitation, and patient education were promising for increasing adherence. Despite positive aspects of improvements in gait, balance in elderly, and a sense of security produced by using assistive devices, compliance remains less than ideal due to barriers. As compliance in recent studies has not improved, continued work in this area is essential to realize the benefits of technological advances in orthotic and assistive devices.

Joint Angle Variability Is Altered in Patients with Peripheral Artery Disease after Six Months of Exercise Intervention.

Supervised exercise therapy (SET) is a conservative non-operative treatment strategy for improving walking performance in patients with peripheral artery disease (PAD). Gait variability is altered in patients with PAD, but the effect of SET on gait variability is unknown. Forty-three claudicating patients with PAD underwent gait analysis before and immediately after a 6-month SET program. Nonlinear gait variability was assessed using sample entropy, and the largest Lyapunov exponent of the ankle, knee, and hip joint angle time series. Linear mean and variability of the range of motion time series for these three joint angles were also calculated. Two-factor repeated measure analysis of variance determined the effect of the intervention and joint location on linear and nonlinear dependent variables. After SET, walking regularity decreased, while the stability remained unaffected. Ankle nonlinear variability had increased values compared with the knee and hip joints. Linear measures did not change following SET, except for knee angle, in which the magnitude of variations increased after the intervention. A six-month SET program produced changes in gait variability toward the direction of healthy controls, which indicates that in general, SET improved walking performance in individuals with PAD.

Claudicating patients with peripheral artery disease have meaningful improvement in walking speed after supervised exercise therapy.

OBJECTIVE: Supervised exercise therapy (SET) is a first-line treatment for patients with peripheral artery disease (PAD). The efficacy of SET is most commonly expressed by significant statistical improvement of parameters that do not clarify how each individual patient will benefit from SET. This study examined the minimal clinically important difference (MCID) in walking speed in claudicating patients with PAD after SET. METHODS: A total of 63 patients with PAD-related claudication (Fontaine stage II PAD) participated in a 6-month SET program. Self-selected walking speed was measured before and after SET. Distribution and anchor-based approaches were used to estimate the MCID for small and substantial improvement. The ability to walk one block and the ability to climb one flight of stairs questions were chosen as anchor questions from the Medical Outcomes Study 36-item Short Form questionnaire. Receiver operating characteristics curve analyses were performed to detect the threshold for MCID in walking speed after treatment. RESULTS: The distribution-based method estimated 0.03 m/s as a small improvement and 0.08 m/s as a substantial improvement after SET. Small and substantial improvements according to the anchor question walking one block were 0.05 m/s and 0.15 m/s, respectively. For the climbing one flight of stairs anchor question, 0.10 m/s was a small improvement. Receiver operating characteristics curve analyses identified an increase of 0.04 m/s and 0.03 m/s for improvement based on walking one block and climbing one flight of stairs, respectively. CONCLUSIONS: We report our findings for the MCID for walking speed among claudicating patients receiving SET. Claudicating patients who increase walking speed of 0.03 m/s or greater are more likely to experience a meaningful improvement in walking impairment than those who do not. The MCID reported in this study can serve as a benchmark for clinicians to develop goals and interpret clinically meaningful progress in the care of claudicating patients with PAD.

Supervised walking exercise therapy improves gait biomechanics in patients with peripheral artery disease.

OBJECTIVE: In patients with peripheral artery disease (PAD), supervised exercise therapy is a first line of treatment because it increases maximum walking distances comparable with surgical revascularization therapy. Little is known regarding gait biomechanics after supervised exercise therapy. This study characterized the effects of supervised exercise therapy on gait biomechanics and walking distances in claudicating patients with PAD. METHODS: Forty-seven claudicating patients with PAD underwent gait analysis before and immediately after 6 months of supervised exercise therapy. Exercise sessions consisted of a 5-minute warmup of mild walking and stretching of upper and lower leg muscles, 50 minutes of intermittent treadmill walking, and 5 minutes of cooldown (similar to warmup) three times per week. Measurements included self-perceived ambulatory limitations measured by questionnaire, the ankle-brachial index (ABI), walking distance measures, maximal plantar flexor strength measured by isometric dynamometry, and overground gait biomechanics trials performed before and after the onset of claudication pain. Paired t-tests were used to test for differences in quality of life, walking distances, ABI, and maximal strength. A two-factor repeated measures analysis of variance determined differences for intervention and condition for gait biomechanics dependent variables. RESULTS: After supervised exercise therapy, quality of life, walking distances, and maximal plantar flexor strength improved, although the ABI did not significantly change. Several gait biomechanics parameters improved after the intervention, including torque and power generation at the ankle and hip. Similar to previous studies, the onset of claudication pain led to a worsening gait or a gait that was less like healthy individuals with a pain-free gait. CONCLUSIONS: Six months of supervised exercise therapy produced increases in walking distances and quality of life that are consistent with concurrent improvements in muscle strength and gait biomechanics. These improvements occurred even though the ABI did not improve. Future work should examine the benefits of supervised exercise therapy used in combination with other available treatments for PAD.

A low-cost, wireless near-infrared spectroscopy device detects the presence of lower extremity atherosclerosis as measured by computed tomographic angiography and characterizes walking impairment in peripheral artery disease.

BACKGROUND: Patients with peripheral artery disease (PAD) who experience intermittent claudication report a range of symptoms. Patients with symptoms other than classically described intermittent claudication may be at the highest risk for functional decline and mobility loss. Therefore, technologies allowing for characterization of PAD severity are desirable. Near-infrared spectroscopy (NIRS) allows for measurements of muscle heme oxygen saturation (StO2) during exercise. We hypothesized lower extremities affected by PAD would exhibit distinct NIRS profiles as measured by a low-cost, wireless NIRS device and that NIRS during exercise predicts walking limitation. METHODS: We recruited 40 patients with PAD and 10 control participants. All patients with PAD completed a computed tomographic angiography, 6-minute walk test, and a standardized treadmill test. Controls completed a 540-second treadmill test for comparison. StO2 measurements were continuously taken from the gastrocnemius during exercise. Variables were analyzed by Fischer's exact, χ2, Wilcoxon rank-sum, and Kruskal-Wallis tests as appropriate. Correlations were assessed by partial Spearman correlation coefficients adjusted for occlusive disease pattern. RESULTS: Patients with PAD experienced claudication onset at a median of 108 seconds with a median peak walking time of 288 seconds. The baseline StO2 was similar between PAD and control. The StO2 of PAD and control participants dropped below baseline at a median of 1 and 104 seconds of exercise, respectively (P < .0001). Patients with PAD reached minimum StO2 earlier than control participants (119 seconds vs 522 seconds, respectively; P < .001) and experienced a greater change in StO2 at 1 minute of exercise (-73.2% vs 8.3%; P < .0001) and a greater decrease at minimum exercise StO2 (-83.4% vs -16.1%; P < .0001). For patients with PAD, peak walking time, and 6-minute walking distance correlated with percent change in StO2 at 1 minute of exercise (r = -0.76 and -0.67, respectively; P < .001) and time to minimum StO2 (r = 0.79 and 0.70, respectively; P < .0001). CONCLUSIONS: In this initial evaluation of a novel, low-cost NIRS device, lower extremities affected by PAD exhibited characteristic changes in calf muscle StO2, which differentiated them from healthy controls and were strongly correlated with walking impairment. These findings confirm and expand on previous work demonstrating the potential clinical value of NIRS devices and the need for further research investigating the ability of low-cost NIRS technology to evaluate, diagnose, and monitor treatment response in PAD.

Quantification of Daily Physical Activity and Sedentary Behavior of Claudicating Patients.

BACKGROUND: Claudication is the most common manifestation of peripheral artery disease (PAD), producing significant ambulatory compromise. Limited information exists on the routine physical activity of claudicating patients. Our objective was to record the intensity/time profiles of physical activity and the timing and duration of sedentary behavior of a sample of community-dwelling claudicating patients. METHODS: Forty-four claudicating patients referred to our vascular clinic were recruited. Physical activity was recorded using the ActiGraph GT1M activity monitor. The Actigraph monitor is a lightweight instrument designed to measure human movement through changes in acceleration, measured as counts over 1-minute time periods. Data from 7 consecutive days were used for the calculations. We processed the data using the ActiLife software program. RESULTS: The average daily activity of the claudicating patients shows a steady increase beginning approximately 05:30 AM until a peak plateau from approximately 10:00 AM to 01:30 PM followed by a steady decrease until approximately 09:30 PM, when a sustained period of inactivity begins. The average claudicating patient takes 3586 steps per day at an average intensity of 1.77 metabolic equivalents of task (METs, a physiological measure expressing the energy cost of physical activities). Average physical activity intensity and peak intensity fluctuate very little during the day, and they rarely exceed the level of light activity (light = <3 METs maximum effort, such as casual walking or light housework). During awake time, approximately 7 hours are spent in sedentary behaviors (<1.5 METs), and sedentary time is spread throughout the day mostly in short intervals between periods of low-energy activity. CONCLUSIONS: Our study objectively demonstrates the reduced physical activity of claudicating patients and documents physical activity/duration profiles throughout the day. The intensity of the physical activity of the average claudicating patient fluctuates very little during the day and rarely exceeds a light intensity level. Claudicating patients spend approximately half of their awake time in sedentary behavior and when they walk they do it in short bursts followed by several minutes of rest. We anticipate that changes in routine physical activity/duration profiles of patients with PAD will provide relevant, sensitive, and direct measures of the effectiveness of therapeutic interventions.

Optic flow improves step width and length in older adults while performing dual task.

BACKGROUND: Dual-task paradigms are used to investigate gait and cognitive declines in older adults (OA). Optic-flow is a virtual reality environment where the scene flows past the subject while walking on a treadmill, mimicking real-life locomotion. AIMS: To investigate cost of environment (no optic-flow v. optic-flow) while completing single- and dual-task walking and dual-task costs (DTC; single- v. dual-task) in optic-flow and no optic-flow environments. METHODS: Twenty OA and seven younger adults (YA) walked on a self-paced treadmill in 3-min segments per task and both environments. Five task conditions included: no task, semantic fluency (category), phonemic fluency (letters), word reading, and serial-subtraction. RESULTS: OAs had a benefit of optic-flow compared to no optic-flow for step width (p = 0.015) and step length (p = 0.045) during letters compared to the YA. During letters, OA experienced improvement in step width DTC; whereas YA had a decrement in step width DTC from no optic-flow to optic-flow (p = 0.038). During serial-subtraction, OA had less step width DTC when compared to YA in both environments (p = 0.02). DISCUSSION: During letters, step width and step length improved in OA while walking in optic-flow. Also, step width DTC differed between the two groups. Sensory information from optic-flow appears to benefit OA. Letters relies more on verbal ability and word knowledge, which are preserved in aging. However, YA use a complex speech style during dual tasking, searching for complex words and an increased speed of speech. CONCLUSIONS: OA can benefit from optic-flow by improving spatial gait parameters, specifically, step width, during dual-task walking.