Tendon Reflex Hammer
QUANTIFIED DEEP TENDON REFLEX DEVICE FOR RESPONSE AND LATENCY, THIRD GENERATION
Abstract: The deep tendon reflex is fundamental for a neurological examination. A hyperactive reflex response is correlated with spasticity, which also can be associated with the degree of damage to the supraspinal input, essentially assessing the severity of traumatic brain injury. Clinical evaluation of the myotatic stretch reflex is provided by the NINDS reflex scale (0 to 4). The results of the NINDS reflex scale vary in terms of interpretation and lack temporal data. Deep tendon reflex can assess the severity and degree of peripheral neuropathy. Subsequent to the neurological examination, suspect patients are often referred to a specialist for definitive electrodiagnostic testing. A study by Cocito found that 28% of the prescriptions for testing were considered to be not appropriate. The solution is a fully quantified tendon reflex evaluation system. The input force of the reflex hammer is derived from a predetermined potential energy setting. Tandem wireless 3D MEMS accelerometers quantify the output and latency time of the reflex. The wireless 3D MEMS accelerometers are positioned to a standard anchor point near the ankle and reflex hammer swing arm. Reflex response is quantified by the maximum and minimum components of the acceleration profile. The temporal disparity between hammer strike and response defines the latency of the reflex loop. The quantified data collected from wireless 3D MEMS accelerometers is conveyed to a portable computer or handheld device. Enclosed are the initial test and evaluation and the description of a device, which quantitatively evaluates the reflex response and latency using accelerometers, while demonstrating precision for reproducibility.
Struggling with your essay?
Keywords: Reflex quantification, accelerometers, neurorehabilitation, traumatic brain injury
The clinical utility of the tendon reflex, such as the Patellar and Achilles tendon, is attributed to the ability to evaluate the functional disturbance for the reflex arc, both nominal or augmented; and motor system assessment.1, 2, 3 The tendon reflex is useful for the evaluation of various neurological/neuromuscular disorders. 1, 2, 3 The tendon reflex response is important from an experimental perspective because of the sensitivity to facilitating and inhibiting influences; such as during upper motor neuron syndrome acute, subacute, and chronic stages. 1, 4, 5 The reflex latency derives measurement of nerve conduction.6 Two reflex parameters latency and amplitude represent the severity of the pathophysiological mechanisms due to lesion.1
An evaluation of the NINDS Myotatic Reflex Scale consisted of 80 subjects. The experiment determined that intraobserver reliability was substantial to near perfect agreement and moderate to substantial agreement interobserver for the NINDS Myotatic Reflex Scale.7 However a study by Manschot and colleagues contradicts the claim that the NINDS Myotatic Reflex Scale is capable of providing even moderate agreement. A notable issue is the NINDS Myotatic Reflex Scale consists of only a five component ordinal scale. The Manschot study found the agreement between doctors was never greater the “fair” for both scales, and the highest κ statistics value was 0.35.8
The solution is a fully quantified tendon reflex evaluation system. The force input of the reflex hammer will be based on original potential energy. A wireless 3D MEMS accelerometer will quantify the output. The wireless 3D MEMS accelerometer is positioned to a set anchor point near the ankle, above the lateral aspect of the leg to the medial maleolus. The reflex response acceleration waveform can be temporally averaged by integrating acceleration from initial time to final time, or through obtaining significant parameters of the acceleration profile, such as the maximum or minimum acceleration for the reflex response. Quantified data obtained from the wireless 3D MEMS accelerometer is transmitted by a laptop computer.
Original studies involved assessing the maximal acceleration of the reflex response using the Mednode device which is suitable for use as a wearable device. The Mednode device is wireless, therefore minimally restrictive.9 The results from the original studies consisted of a total of 108 measurements; and the relative variation of 107 measurements for the quantified amplitude of reflex response was bounded by a maximum relative variation of 10%. Only one measurement for the quantified amplitude of reflex response exceeded the 10% bound with a maximum relative variation bound of 15%. These findings demonstrate it is possible to quantify deep tendon reflex response with the quantified reflex device using wireless 3D MEMS accelerometers.10, 11, 12
Since the original study, the quantified reflex device has been upgraded. Fully wireless 3D MEMS accelerometers from Microstrain have been integrated. The Microstrain wireless 3D MEMS accelerometers are capable of synchronized data streams, with a variety of sample frequencies.13
The device is developed for maximizing reproducibility. The fundamental components of the device are a swing arm for quantifying input and a wireless 3D MEMS accelerometer for measuring reflex response. With a wireless 3D MEMS accelerometer also attached to the swing arm the reflex latency can be derived from the time disparity between the acceleration profile of reflex response and acceleration profile of swing arm strike. The objective of this application is to develop and evaluate such a device which measures deep tendon reflex amplitude and latency for the patellar tendon with a high degree of reliability and reproducibility.
2. General neuroanatomy and significance of the reflex response and latency
The tendon reflex is essentially a mechanical counterpart of the H-reflex. The tendon reflex is evoked by tapping a tendon, stimulating muscles spindle 1a afferents. These afferent impulses are conveyed to the spinal cord. In the spinal cord the 1a afferents synapse with alpha motor neurons. Subsequent efferent signals are conveyed to their respective muscle resulting in a short contraction. The reflex arc was originally proposed to be monosynaptic, but oligosynaptic contributions to the reflex arc have been discovered.1, 14
For research, improved fidelity for spasticity assessment will allow for quantification of responses to therapy. From a clinical perspective treatment of spasticity using drugs could be optimized. A reliable and fully quantified device for assessing the input and response of the deep tendon reflex would allow for the quantification of the clinical deep tendon examination and provide a means of quantifying research studies in the field of upper motor neuron syndrome.1
This essay is an example of a student's work
Several lower and upper limb tendons are amenable for evoking reflexes for healthy subjects. Generally the tendon reflex is elicited from the lower limb, such as the knee (Patellar tendon reflex) and ankle (Achilles tendon reflex).1
The reflex latency is a basic means to assess nerve conduction.6 The clinical relevance of the patellar tendon reflex is based on clinicians' use of this reflex to evaluate the status of the nervous system. 1, 2, 3, Traditionally the patellar reflex has been used to assess neurological and neuromuscular disorders, particularly as applied to peripheral neuropathy. 1, 2, 3, 15 This syndrome produces extended latency of stretch reflexes. This is primarily correlated to damage to the myelin sheath of the nerve fiber.15
A study by Cocito and colleagues assessed the appropriateness of prescribing electrodiagnostic evaluation. The appropriateness of the prescriptions was based on the percentage of subjects who actually need an electrodiagnostic examination in consideration of the results. The study consisted of 3900 subjects for electrodiagnostic evaluation. 72% of the prescriptions were considered to be an appropriate allocation of resources, however 28% of the electrodiagnostic studies were considered to be unnecessary. In addition 60% of the initial referring diagnoses were changed based on the electrodiagnostic studies.16
Testing the tendon reflex is a simple process, which involves minimal allocation of resources. The patellar tendon reflex is readily elicited. In the study by Kuruoglu, the tendon reflex latency was successfully used as an indicator for demyelinating peripheral neuropathy. The tendon reflex is a useful means for diagnosing demyelinating neuropathies, since the tendon reflex provides information about sensory nerve fibers and motor nerve fibers.15, 17 The simplicity of the tendon reflex evaluation contrasts relative to the specialized training required to perform electrodiagnostic testing.18
3. Previous concepts
Previous concepts have been assessed as similar to the present concept of quantified deep tendon reflexes using wireless 3D MEMS accelerometers. However although also novel the presented reflex quantification device is established as having greater utility, both in terms of scalability and non-intrusiveness. A number of other devices have been developed to quantify deep tendon reflexes. These systems include devices developed by Pagliaro and Zamparo, Cozens, Van de Crommert, Faist, Lebiedowska, Mamizuka, EMG evaluation, and NeuroMetrix, Inc.
The research group of Pagliaro and Zamparo quantified tendon reflex input and output response. The tendon reflex input is originated from an instrumented hammer developed by PCB Piezotronics Inc., USA. The tendon reflex response is evaluated by connecting the ankle to a load cell through an inextensible cable. The load cell and cable alignment enabled the measurement of the force component in the direction normal to the leg.19
Although the tendon hammer instrumentation reliably quantified input, two aspects of variability are introduced to the system. The clinician would inherently have variation of both the input magnitude and accuracy of input impact on the patellar tendon. The measurement of the reflex response involves restrictive devices, since the load cell is connected to the ankle by a cable. The load cell can not measure the full temporal nature of the reflex response, only accurately measuring the maximal force from the reflex response.
The device developed by Cozens evoked the biceps brachii stretch reflex using a servo-positioned tendon hammer. Surface EMG measured the amplitude of the stretch reflex. Cerebral dysfunction from brain injury is associated with abnormal myotatic reflexes. With this device the biceps brachii stretch reflex can be evaluated at bedside during the acute phases of brain injury. The reflex measurements can assist with the monitoring of head injured patients.20
However the most significant contrast with respect to the device developed by Cozens and the proposed reflex quantification device is the intended subject group. The intended subject group is acute brain injured subjects, generally in intensive care and comatose, for the device by Cozens. The biceps brachii tendon reflex is measured, instead of the patellar tendon reflex. Given the subject group is generally bed confined, the biceps brachii tendon reflex would be preferable for tendon reflex measurement. A notable finding by Cozens is the inverse correlation of GCS score with abnormality of tendon reflex response.20
Van de Crommert developed a device which integrated a quantified input device and output reflex response with EMG measurements. The tendon reflex input was evoked using a magnetic motor to actuate a reflex hammer. A mass of approximately one kilogram was attributed to the magnetic motor with reflex hammer input device. The input device elicited the reflex of the biceps femoris tendon by positioning the device to the back of the leg.21 A subsequent study by Faist placed the input device at the anterior section of the calf. The motor consisted of a potentiometer, which could determine the reflex hammer impact and movement.22
Freelance Essay Writing Vacancies
Looking to become a writer?
Due to high demand for our services we're always looking for new writers. If you're interested in becoming a freelance writer then why not read more about our freelance writer jobs.
The quantified input from the device involves a mechanized input which is similar to the quantified deep tendon reflex device using wireless 3D accelerometers; however, the inherent attributes and functional intent of the device are disparate. Tendon reflexes are evoked by the motorized input device during gait cycle. Because of the functional disparity of both input devices, the input device with motor must be positioned on the lower limb of the subject. The motorized input device results in a one kilogram load on the calf perturbing the tendon reflex response.
Another study for reflex quantification was conducted by Lebiedowska. The input quantification involved a sweep-triggering hammer, which was equipped with a strain-gauge accelerometer and manually operated. A strain gauge beam attached to the ankle joint measured patellar tendon reflex response. A notable difference is the experiment involved biofeedback, instructing the subject to exert a certain load, parameterized as a percentage of maximum voluntary contraction.23
The study discovered that the reflex response curves as a function of percentage of maximum voluntary contraction are disparate while contrasting nominal neurology subjects to brain injured subjects. The research of Lebiedowska is a fundamental improvement for the quantification of reflexes.23 The sweep triggered hammer quantified input device lacks the variability of the swing arm potential energy variable hammer input of the wireless 3D MEMS accelerometer reflex quantification reflex device. The wireless 3D MEMS accelerometer can obtain temporal characteristics for the complete reflex response. Instead of subject compliance with biofeedback requirements, the wireless 3D MEMS accelerometer reflex quantification reflex device allows for simplified variable hammer strike inputs at specific potential energy settings.
A reflex quantification device developed by Mamizuka does use a triaxial accelerometer to quantify the patellar tendon reflex response. However the device by Mamizuka is not wireless like the Microstrain wireless 3D MEMS accelerometer. The device by Mamizuka uses an instrumented reflex hammer, but the reflex hammer lacks a predetermined quantified input setting.24
Nerve conduction studies are a correlated component of EMG evaluation. Electrodes are positioned on the skin over the nerve to be evaluated. Instrumentation measures the time elapsed for the electrical impulse to convey to another electrode on the nerve.25 The reflex latency allows measurement of nerve conduction, which is a less resource intensive alternative.6
Another cutting edge device is the NC-stat System developed by the company Neurometrix. The NC-stat System device performs a non-invasive nerve conduction evaluation. The reliability of this device has also been established. The patellar tendon reflex evaluation also addresses supraspinal input and modulation with the entire afferent and efferent components of the reflex loop. The Neurometrix device is designed to evaluate nerve conduction of a highly localized portion of the peripheral nervous system, which is more suitable for evaluating carpal tunnel syndrome.26
4. Quantified deep tendon reflex device
The design theme of the device is to maximize reproducibility. A prototype system was designed and built consisting of a swing arm, Microstrain wireless 3D MEMS accelerometers, and reflex hammer. Communication between system components is wireless and does not limit or restrict movement. The essential components of the device are the variable position swing arm with the wireless 3D MEMS accelerometer for quantifying input and a wireless 3D MEMS accelerometer for measuring reflex response. The sampling rate for both accelerometers was set to 100Hz. The following picture characterizes the quantified deep tendon reflex device.
Figure 1. Prototype of the device for quantifying reflex response and latency
The design of the swing arm allows for quantified input based on settings of variable potential energy. The end of the swing arm is fastened to a standard neuro-reflex hammer for eliciting tendon reflexes of the patella. The swing arm position can be fixed to strike a specific point on the tendon. The swing arm is raised to a given angle such as 30 degrees, and allowed to drop. The hammer strikes the patellar tendon with a known force. The design allows for studies of variable input intensity.
The swing arm component is secured to a linearly translating mast. The linear translation may occur vertically and horizontally in a plain parallel to the gravity vector using two adjustable knobs, which allows for the fastened reflex hammer to be precisely aimed evoking the tendon reflex. The swing arm may also translate using an adjustable knob, which provides the autonomy to vary the moment arm if necessary. A protractor is mounted to the device for specific quantified input, such as a 30 degree setting. The mast of the swing arm is secured by a heavy counter weight at the base. A wireless 3D accelerometer is secured to the swing arm providing the acceleration profile of the impact of the swing arm.
The wireless 3D accelerometer provides the means to quantify the intensity of the reflex response. The wireless 3D accelerometer is placed in a constant anatomical location to improve the reproducibility of the measurement. The signal of wireless 3D accelerometer is conveyed wirelessly to a local portable personal computer for data storage and processing. Data is processed through the PC.13
The selection of the wireless 3D accelerometer was a critical aspect of developing the third generation quantified deep tendon reflex device for response and latency. There are multiple significant criteria for the wireless 3D accelerometers. The wireless data must be capable of being conveyed at a reasonable distance with respect to the placement of the wireless 3D accelerometers and the personal computer for data storage and processing. The accelerometers must be light weight. The signals of both wireless 3D accelerometers must be synchronized, in order to effectively measure latency in units of milliseconds. The software for operating the wireless 3D accelerometers should be readily manageable for the user. Three wireless 3D accelerometers were considered for the third generation quantified deep tendon reflex device for response and latency.
First for consideration was the Mednode wireless 3D accelerometer. The Mednode has been successfully tested and evaluated for measuring reflex response. 10, 11, 12, 27, 28 The signal of the 3D accelerometer Mednode is conveyed wirelessly to a local portable personal computer for data storage and processing. The Mednodes are software programmable, which allows great flexibility for this application. Data may be processed by PC.9 However during initial testing and evaluation for measuring latency, the Mednode wireless 3D accelerometers had difficulty with synchronicity and wireless signal strength.
Another wireless 3D accelerometer developed by SparkFun Electronics was considered for the third generation quantified deep tendon reflex device for response and latency. The wireless signal strength was sufficient with a 30 meter indoor range. The SparkFun Electronics wireless 3D accelerometer required a 4 AA battery power source, which negatively impacts packaging and minimal mass requirements. The software for operating the SparkFun Electronics wireless 3D accelerometer was also cumbersome for general user and lacked the inherent ability to synchronize two simultaneous streams of wireless accelerometer data.29
The most preferable 3D wireless accelerometer for the third generation quantified deep tendon reflex device for response and latency is the G-Link® Wireless Accelerometer Node. The G-Link® Wireless Accelerometer Node is capable of supporting simultaneous data streams to a common PC. The accelerometer is light with a mass of 46 grams, and powered by its own rechargeable battery. The wireless signal strength is 70 meters line of sight. The software platform for operated the G-Link® Wireless Accelerometer Node is suitable for the users and involves a graphic user interface.13
The system requires no placement of EMG electrodes or tethering of the leg. To test the feasibility of the design proposed in this application we evaluated the performance of the device with two subjects. Instead of the complexity of placing EMG electrodes, the reflex response is measured simply by attaching a wireless 3D accelerometer to the lower leg. The swing arm can be targeted to a contact point to ensure input accuracy. To test the feasibility of the design we evaluated the device with two subjects.
The initial test and evaluation for the device study consisted of two subjects; one subject had nominal neurology and one subject was a chronic hemiplegic. The tests were performed using the following protocol:
- Place the wireless 3D accelerometer with an elastic band on the lateral aspect of the leg to the medial maleolus.
- Aim the patellar tendon hammer at the level of the tibial tubercle.
- Pull back the swing arm to a predetermined angle of 30 degrees from an initial position.
- Release the swing arm.
- Record the wireless 3D MEMS accelerometer data.
- Include a minimum of one minute delay before the next patellar tendon hammer strike.20
- Repeat the protocol.
The experiment consisted of two sets of measurements at the 30 degree input level. Given two subjects being tested with one leg, on the same side as the preferred arm for the nominal neurology subject and the unaffected leg for the chronic hemiplegic subject, for 20 measurements, a total of 40 measurements were obtained. The intent of the experiment is to demonstrate engineering proof of concept. The initial study was intended to ascertain the reliability of the fully quantified deep tendon reflex device to demonstrate the ability to quantify the deep tendon reflex response and latency.
6. Results and Discussion
6.1. Preliminary results
A prototype reflex quantification system was developed consisting of a swing arm, two Microstrain wireless 3D MEMS accelerometers, and reflex hammer. Communication between the system components is wireless while not limiting or restricting movement. The intent of this system was to use the wireless 3D MEMS accelerometers and associated hardware to develop a reliable means of quantifying the patellar tendon reflex response and latency.
The tendon reflex input is based on predetermined potential energy settings from the swing arm. The intensity of the input strike is highly consistent. The friction for the joint of the swing arm is minimal. The height of the swing arm before release is predetermined and repeatable. The swing arm is mounted to a variable position stand which allows for reliable input impact on the same point on the patellar tendon. The hammer can be first aimed. Then the swing arm connected to the hammer can be pulled back to the desired potential energy setting. The reflex quantification system can repeat the same precise energy and strike position. The reflex response output is measured by the wireless 3D MEMS accelerometer, which transmits information to a portable computer using wireless connectivity. The device measures output nonintrusively, as the reflex quantification system has minimal mass bias. The wireless 3D MEMS accelerometer can reliably measure the complete reflex response temporal acceleration waveform. This should be an advancement over other existing reflex quantification devices. With a Microstrain wireless 3D MEMS accelerometer also attached to the swing arm the reflex latency can be obtained by the time disparity between acceleration profile of the reflex response and acceleration profile of swing arm reflex hammer strike.
6.2. Test and evaluation results:
Data was further processed by converting the voltage signal to g's of gravity for the calculation of minimum and maximum response. Reflex latency was based on the temporal disparity between the characteristic initial swing arm reflex hammer strike and the initial minimum response. The following six graphs consist of the minimum and maximum reflex response calibrated to g's of gravity acceleration and reflex latency in units of msec. 20 trials were conducted on both subject 1 a chronic hemiplegic and subject 2 with nominal neurology. The unaffected lower limb was selected for measurement for subject 1, and the lower limb on the same side as the preferred arm was selected for subject 2.
Graph 1. Subject 1 (chronic hemiplegic) Reflex latency 30 degree swing arm input
Graph 2. Subject 1 (chronic hemiplegic) Minimum reflex response 30 degree swing arm input
Graph 3. Subject 1 (chronic hemiplegic) Maximum reflex response 30 degree swing arm input
Graph 4. Subject 2 (nominal neurology) Reflex latency 30 degree swing arm input
Graph 5. Subject 2 (nominal neurology) Minimum reflex response 30 degree swing arm input
Graph 6. Subject 2 (nominal neurology) Maximum reflex response 30 degree swing arm input
Graphs 1 through 6 characterize inherent consistency of the quantified reflex maximum response, minimum response, and latency. Graph 1 through 3 represent the chronic hemiplegic subject's unaffected leg. Graphs 4 though 6 represent subjects with nominal neurology for the subject's leg on the same side as the preferred arm.
The results are based on a total of 40 measurements. The results demonstrate consistent quantified reflex parameters. Table 1 summarizes the quantified reflex parameters for subject 1 and 2.
Table 1. Quantified reflex parameters
Reflex latency mean
Reflex latency standard of deviation (msec)
Maximum reflex response mean (g's)
Maximum reflex response standard of deviation
Minimum reflex response mean (g's)
Minimum reflex response standard of deviation
A statistical analysis was subsequently conducted to define the confidence level bounds based on a sample of 20 measurements per subject. Reflex latency was selected as the bounding parameter, since reflex latency had more variation relative to maximum and minimum reflex response. A sample size of 20 measurements is bounded with a confidence level of 95%, based on a 5% margin of error relative to the mean. Experiment time could be further conserved with a sample size of 10 measurements. Based on the available data for the reflex quantification device, a sample size of 10 could be bounded with a 90% confidence level and a 5% margin of error relative to the mean.30
These findings suggest it is possible to quantify deep tendon reflex using the proposed device. Determination of reproducibility of the measurement requires further testing. Given the initial results, further trials may be warranted to further establish the reproducibility of the measurement technique. The goal of initial clinical trials will be to assess the reproducibility of the device for quantifying deep tendon reflexes.
The deep tendon reflex is a fundamental aspect of the neurological examination. However, there are inherent issues of accuracy with present methods for the quantification of the reflex response, such as the NINDS reflex scale. The quantified deep tendon reflex device proposed demonstrated quantified input of tendon reflex strike with quantified assessment of reflex maximum response, minimum response, and latency. The preliminary test and evaluation of the reflex quantification device implicates a considerable degree of accuracy and reproducibility. A confidence level of 95% was ascertained, based on a 5% margin of error relative to the mean bounded a sample size of 20 measurements per subject. Based on the data obtained, an experiment may be reduced to a sample size of 10 measurements with a bound of a 90% confidence level and a 5% margin of error relative to the mean. In consideration of the initial results, further testing and evaluation is warranted, such as a clinical trial.
7.1. Advanced implications
Upon clinical validation for reproducibility, the wireless 3D reflex quantification device can be extended into the field of gait analysis. During nominal gait cycle, reflex modulation is considered to be significant from a functional perspective. In contrast to healthy subjects, patients with hemiparesis have reduced reflex modulation for the affected side. For subjects with hemiparesis gait cycle is generally asymmetric.22 Assuming the constraint of equivalent tendon reflex inputs; the reflex response is disparate for the unaffected vs. affected lower limb for hemiparetics.23 The device can measure the characteristics of reflex modulation of the unaffected and affected leg for hemiparetics. The quantified evaluation of deep tendon reflex modulation based on variable quantified input using stationary conditions could be used to assess gait disparity for hemiparetics. Peripheral neuropathies may be assessed and tracked in a far less resource intensive manner using the proposed quantified reflex device. Due to the limited availability and cost of electrodiagnostic testing, a system that allows quantification of the myotatic reflex might offer an improved method for patient selection prior to referral for electrodiagnostic testing.
In order to further substantiate the novelty of the third generation quantified deep tendon reflex device, the initial aspects of the concept were disclosed in a UCLA Neuroengineering graduate class during June 2005.31 The concept for the quantified deep tendon reflex device has been presented multiple times at the 15th International Conference on Mechanics in Medicine and Biology during 2006 and also at the 35th, 36th, and 37th Society for Neuroscience.10, 11, 27, 28
Instrumental has been the support from the UCLA IGERT NSF fellowship.
Provisional patents filed
UCLA Case No. 2007-494; “Device for Quantifying Deep Tendon Reflex Amplitude and Latency”
UC Case No. 2006-288; “Fully quantified evaluation of myotatic stretch reflex”
UC Case No. 2006-660; “Quantified Deep Tendon Reflex Device”
1.Voerman GE, Gregoric M, Hermens HJ, Neurophysiological methods for the assessment of spasticity: The Hoffmann reflex, the tendon reflex, and the stretch reflex, Disability and Rehabilitation 27:33-68, 2005.
2.Karandreas N, Piperos P, Dimitriou D, Kokotis P, Zambelis T, Electrophysiological recording of tendon reflexes in cervical myelopathy, Electromyography and Clinical Neurophysiology 40:83-88, 2000.
3.Toft E, Sinkjaer T, Espersen GT, Quantitation of the stretch reflex. Technical procedures and clinical applications, Acta Neurol Scand. 79:384-390, 1989.
4.Hiersemenzel LP, Curt A, Dietz V, From spinal shock to spasticity: neuronal adaptations to a spinal cord injury, Neurology 54:1574 - 1582, 2000.
5.Ko H-Y, Ditunno JF, Graziani V, Little JW, The pattern of reflex recovery during spinal shock, Spinal Cord 37:402 - 409, 1999.
6.Frijns CJ, Laman DM, van Duijn MA, van Duijn H, Normal values of Patellar and ankle tendon reflex latencies, Clinical Neurology and Neurosurgery 99:31-36, 1997.
7.Litvan I, Mangone CA, Werden W, Bueri JA, Estol CJ, Garcea DO, Rey RC, Sica REP, Hallett M, Bartko JJ, Reliability of the NINDS myotatic reflex scale, Neurology 47:969-972, 1996.
8.Manschot S, Van Passel L, Buskens E, Algra A, Van Gijn J, Mayo and NINDS scales for assessment of tendon reflexes: between observer agreement and implications for communication, Journal of Neurology Neurosurgery Psychiatry 64:253-255, 1998.
9.Jafari R, Encarnacao A, Zahoory A, Dabiri F, Noshadi H, Sarrafzadeh M, Wireless sensor networks for health monitoring, The 2nd ACM/IEEE International Conference on Mobile and Ubiquitous Systems (MobiQuitous) San Diego, 2005.
10.LeMoyne R, Jafari R, Quantified Deep Tendon Reflex Device, Second Generation, 15th International Conference on Mechanics in Medicine and Biology, 2006.
11.LeMoyne R, Jafari R, Quantified deep tendon reflex device, 36th Society for Neuroscience, 2006.
12.LeMoyne R, Dabiri F, Jafari R, Quantified Deep Tendon Reflex Device, Second Generation, Journal of Mechanics in Medicine and Biology, 8: 75-85, 2008.
14. Kandel ER, Schwartz JH, Jessell TM, Principles of Neural Science, McGraw-Hill, New York, fourth edition, 2000.
15.Kuruoglu HR, Oh SJ, Tendon-reflex testing in chronic demyelinating polyneuropathy, Muscle Nerve 17:145-150, 1994.
16.Cocito D, Tavella A, Ciaramitaro P, Costa P, Poglio F, Paolasso I, Duranda E, Cossa FM, Bergamasco B, A further critical evaluation of requests for electrodiagnostic examinations, Neurological Sciences 26: 419-422, 2006
17.van Dijk GW, Wokke JH, Notermans NC, van Gijn J, Franssen H, Diagnostic value of myotatic reflexes in axonal and demyelinating polyneuropathy, Neurology 53:1573-1576, 1999.
19.Pagliaro P, Zamparo P, Quantitative evaluation of the stretch reflex before and after hydrokinesy therapy in patients affected by spastic paresis, Journal of Electromyography and Kinesiology 9:141-148, 1999.
20.Cozens J, Miller S, Chambers I, Mendelow A, Monitoring of head injury by myotatic reflex evaluation, Journal of Neurology Neurosurgery Psychiatry 68:581-588, 2000.
21.Van De Crommert HW, Faist M, Berger W, Duysens J, Biceps femoris tendon jerk reflexes are enhanced at the end of the swing phase in humans, Brain Research 734:341-344, 1996.
22.Faist M, Ertel M, Berger W, Dietz V, Impaired modulation of quadriceps tendon jerk reflex during spastic gait: differences between spinal and cerebral lesions, Brain, 122, pp. 567-579, 1999.
23.Lebiedowska M, Fisk J, Quantitative Evaluation of Reflex and Voluntary Activity in Children With Spasticity, Archives of Physical Medicine and Rehabilitation, 84, pp. 828-837, 2003.
24.Mamizuka N, Sakane M, Kaneoka K, Hori N, Ochiai N, Kinematic quantitation of the patellar tendon reflex using a tri-axial accelerometer, Journal of Biomechanics 40:2107-2111, 2007.
27.LeMoyne R, Jafari R, Jea D, Fully Quantified Evaluation of Myotatic Stretch Reflex, 35th Society for Neuroscience, 2005.
28.LeMoyne R, Dabiri F, Coroian C, Mastroianni T, and Grundfest W, Quantified deep tendon reflex device for assessing response and latency, 37th Society for Neuroscience, 2007.
30. Moore DS, McCabe GP, Introduction to Practice of Statistics, W.H.Freeman and Company, New York, third edition, 1998.
31.LeMoyne R, UCLA communication, NeuroEngineering, 2005.
If you are the original writer of this essay and no longer wish to have the essay published on the UK Essays website then please click on the link below to request removal: