Extraction of time and frequency features from grip force rates during dexterous manipulation

Contributions of the Primary Sensorimotor Cortex and Posterior Parietal Cortex to Motor Learning and Transfer

BACKGROUND

Transferring learned manipulations to new manipulation tasks has enabled humans to realize thousands of dexterous object manipulations in daily life. Two-digit grasp and three-digit grasp manipulations require different fingertip forces, and our brain can switch grasp types to ensure good performance according to motor memory. We hypothesized that several brain areas contribute to the execution of the new type of motor according to the motor memory. However, the motor memory mechanisms during this transfer period are still unclear. In the present functional magnetic resonance imaging (fMRI) study, we aimed to investigate the cortical mechanisms involved in motor memory during the transfer phase of learned manipulation tasks.

METHODS

Using a custom-built T-shaped object with an adjustable weight distribution, the participants performed grasp and lift manipulation tasks under different conditions to simulate the learning and transfer phases. The learning phase consisted of four grasp-and-lift repetitions with one motor type, followed by a transfer phase with four repetitions involving different motors (adding or removing a digit).

RESULTS

By comparing brain activity in the learning and transfer phases, we identified three regions (the superior frontal gyrus, supramarginal gyrus, and postcentral gyrus) associated with motor memory during the transfer of learned manipulations.

CONCLUSIONS

Our findings improve the understanding of the role of the posterior parietal cortex in motor memory, highlighting how sensory information from memory and real-time input is integrated to generate novel motor control signals that guide the precise reapplication of control strategies. Furthermore, we believe that these areas contribute to motor learning from motor memory and may serve as key regions of interest for investigating neurodegenerative diseases.

Object-centered sensorimotor bias of torque control in the chronic stage following stroke

When lifting objects whose center of mass (CoM) are not centered below the handle one must compensate for arising external torques already at lift-off to avoid object tilt. Previous studies showed that finger force scaling during object lifting may be impaired at both hands following stroke. However, torque control in object manipulation has not yet been studied in patients with stroke. In this pilot study, thirteen patients with chronic stage left hemispheric stroke (SL), nine patients with right hemispheric stroke (SR) and hand-matched controls had to grasp and lift an object with the fingertips of their ipsilesional hand at a handle while preventing object tilt. Object CoM and therewith the external torque was varied by either relocating a covert weight or the handle. The compensatory torque at lift-off (Tcom) is the sum of the torque resulting from (1) grip force being produced at different vertical finger positions (∆CoP × GF) and (2) different vertical load forces on both sides of the handle (∆Fy × w/2). When having to rely on sensorimotor memories, ∆CoP × GF was elevated when the object CoM was on the ipsilesional-, but decreased when CoM was on the contralesional side in SL, whereas ∆Fy × w/2 was biased in the opposite direction, resulting in normal Tcom. SR patients applied a smaller ∆CoP × GF when the CoM was on the contralesional side. Torques were not altered when geometric cues were available. Our findings provide evidence for an object-centered spatial bias of manual sensorimotor torque control with the ipsilesional hand following stroke reminiscent of premotor neglect. Both intact finger force-to-position coordination and visuomotor control may compensate for the spatial sensorimotor bias in most stroke patients. Future studies will have to confirm the found bias and evaluate the association with premotor neglect.

Learning of Dexterous Object Manipulation in a Virtual Reality Environment

Humans have unrivalled abilities to perform dexterous object manipulation. This requires the sensorimotor system to quickly adapt to environmental changes and predictively counter act the external disturbances. Many studies have focused on the anticipatory control of digits with real-world experiments. However, examining manipulation using virtual reality with haptic devices expands the possibilities of investigation. In this work, participants grasped and lifted an inverted T-shaped object in a virtual reality setup. The graspable surface of the object was either constrained to a small area or unconstrained. The position of the object's center of mass changed between blocks, and the participants were asked to minimize the rotation of the object during the lift. Our results show that, consistent with the results of real-world experiments, participants gradually learn to adjust the digit positions and forces to predictively compensate for the torque due to the shifted center of mass prior to liftoff. The only major difference found was that the length of trials needed during the adaptation phase to each condition increased from 3 in real-world to 5 in virtual environment.

Brain functional networks analysis of five fingers grasping in virtual reality environment

This study investigated the effects of different center of mass (COM) of the grasping device and visual time-delay on the information interaction between brain regions during five-finger grasping process. Nine healthy right-handed subjects used five fingers to grasp a special device in a virtual reality (VR) environment. Two independent variables were set in the experiment: the COM of the grasping device and the visual delay time. Place a 50 g mass randomly at five different directions of the grasping device base. The three levels of visual delay time appear randomly. The kinematics and dynamics and electroencephalogram (EEG) signals were recorded during the experiment. The brain network was constructed based on multiplex horizontal visibility graph (MHVG). Interlayer mutual information (MI) and phase locking value (PLV) were calculated to quantify the network, while clustering coefficient (C), shortest path length (L) and overall network efficiency (E) are selected to quantify the network characteristic. Statistical results show that when the mass is located in the radial side, during the load phase of grasping, the C and E is significantly higher than that in the proximal, ulnar and medial side, and L was significantly lower than that in the proximal and radial side. This shows that when grasping an object with a COM bias on the radial side, the process of brain feedforward control has higher level of information interaction and ability and it can build stronger sensorimotor memory. It is also found that the brain network features of theta, beta and gamma bands of EEG are positively correlated, especially between beta and gamma bands, which suggests there is a coupling relationship between different bands in information processing and transmission.Clinical Relevance- This study explains the neural mechanism of grasping control from the topological structure of the whole brain network level and the informatics.

Effects of aging on conditional visuomotor learning for grasping and lifting eccentrically weighted objects

Explicit knowledge of object center of mass or CM location fails to guide anticipatory scaling of digit forces necessary for dexterous manipulation. We previously showed that allowing young adults to choose where to grasp the object entailed an ability to use arbitrary color cues about object CM location to gradually minimize object tilt across several trials. This conditional learning was achieved through accurate anticipatory modulation of digit position using the color cues. However, it remains unknown how aging affects the ability to use explicit color cues about object CM location to modulate digit placement for dexterous manipulation. We instructed healthy older and young adults to learn a manipulation task using arbitrary color cues about object CM location. Subjects were required to exert clockwise, counterclockwise, or no torque on the object according to the color cue and lift the object while minimizing its tilt. Older adults produced larger torque error during conditional learning trials, resulting in a slower rate of learning than young adults. Importantly, older adults showed impaired anticipatory modulation of digit position when information of the CM location was available via explicit color cues. The older adults also did not modulate their digit forces to compensate for this impairment. Interestingly, however, anticipatory modulation of digit position was intact in the same individuals when information of object CM location was implicitly conveyed from trial-to-trial. We discuss our findings in relation to age-dependent changes in processes and neural network essential for learning dexterous manipulation using arbitrary color cue about object property.NEW & NOTEWORTHY We studied whether older adults are able to predictively modulate digit position using arbitrary color cues indicating object center of mass location for dexterous manipulation. Older adults showed an impaired ability to modulate digit position using the color cues when compared with young adults. Interestingly, similar impairments were not found when same older individuals learned the task using implicit knowledge. Our findings suggest an age-related impairment specifically in the conditional learning mechanisms for dexterous manipulation.

Transfer and generalization of learned manipulation between unimanual and bimanual tasks

Successful object manipulation, such as preventing object roll, relies on the modulation of forces and centers of pressure (point of application of digits on each grasp surface) prior to lift onset to generate a compensatory torque. Whether or not generalization of learned manipulation can occur after adding or removing effectors is not known. We examined this by recruiting participants to perform lifts in unimanual and bimanual grasps and analyzed results before and after transfer. Our results show partial generalization of learned manipulation occurred when switching from a (1) unimanual to bimanual grasp regardless of object center of mass, and (2) bimanual to unimanual grasp when the center of mass was on the thumb side. Partial generalization was driven by the modulation of effectors' center of pressure, in the appropriate direction but of insufficient magnitude, while load forces did not contribute to torque generation after transfer. In addition, we show that the combination of effector forces and centers of pressure in the generation of compensatory torque differ between unimanual and bimanual grasping. These findings highlight that (1) high-level representations of learned manipulation enable only partial learning transfer when adding or removing effectors, and (2) such partial generalization is mainly driven by modulation of effectors' center of pressure.

Intention to be force efficient improves high-level anticipatory coordination of finger positions and forces in young and elderly adults

Successful object manipulation requires anticipatory high-level control of finger positions and forces to prevent object slip and tilt. Unlike young adults, who efficiently scale grip forces (GFs) according to surface conditions, old adults were reported to exert excessive grip forces. In this study, we theoretically show how grip force economy depends on the modulation of the centers of pressure on opposing grip surfaces (ΔCoP) according to object properties. In a grasp-to-lift study with young and elderly participants, we investigated how the instruction to lift the object with efficient GF influences the anticipation of torques, ΔCoP and GF control during complex variations of mass distributions and surface properties. Provision of the explicit instruction to strive for force efficiency prompted both age groups to optimize their ΔCoP modulation, although to a lesser degree in the elderly, and also led to a refinement of torque anticipation for a right-sided weight distribution in the young, but not the elderly participants. Consequently, marked drops in GF levels resulted. Furthermore, participants enhanced ΔCoP modulation and lowered GF safety ratios in challenging surface conditions. Higher GF in the elderly was due to decreased skin-surface friction but also worse ΔCoP modulation for lateralized mass distributions when trying to be force efficient. In contrast, safety margins were not elevated in the elderly, suggesting preserved GF control. Our findings demonstrate how task goals influence high-level motor control of object manipulation differentially in young and elderly participants and highlight the necessity to control for both instructions and friction when investigating GF control.NEW & NOTEWORTHY Previous studies have shown that forces are covaried as a function of centers of pressure (CoPs) to exert adequate torques. Here, we demonstrate that force-efficient object manipulation requires the modulation of CoPs and show that providing the instruction to be force efficient and challenging surface conditions elicits a GF safety ratio reduction as well as an optimization of anticipatory CoP modulation and torques in the young and, to a lesser degree, in the elderly.

Dexterous Object Manipulation Requires Context-Dependent Sensorimotor Cortical Interactions in Humans

Dexterous object manipulation is a hallmark of human evolution and a critical skill for everyday activities. A previous work has used a grasping context that predominantly elicits memory-based control of digit forces by constraining where the object should be grasped. For this "constrained" grasping context, the primary motor cortex (M1) is involved in storage and retrieval of digit forces used in previous manipulations. In contrast, when choice of digit contact points is allowed ("unconstrained" grasping), behavioral studies revealed that forces are adjusted, on a trial-to-trial basis, as a function of digit position. This suggests a role of online feedback of digit position for force control. However, despite the ubiquitous nature of unconstrained hand-object interactions in activities of daily living, the underlying neural mechanisms are unknown. Using noninvasive brain stimulation, we found the role of primary motor cortex (M1) and somatosensory cortex (S1) to be sensitive to grasping context. In constrained grasping, M1 but not S1 is involved in storing and retrieving learned digit forces and position. In contrast, in unconstrained grasping, M1 and S1 are involved in modulating digit forces to position. Our findings suggest that the relative contribution of memory and online feedback modulates sensorimotor cortical interactions for dexterous manipulation.

Hand forces and placement are modulated and covary during anticipatory control of bimanual manipulation

Dexterous object manipulation relies on the feedforward and feedback control of kinetics (forces) and kinematics (hand shaping and digit placement). Lifting objects with an uneven mass distribution involves the generation of compensatory moments at object lift-off to counter object torques. This is accomplished through the modulation and covariation of digit forces and placement, which has been shown to be a general feature of unimanual manipulation. These feedforward anticipatory processes occur before performance-specific feedback. Whether this adaptation is a feature unique to unimanual dexterous manipulation or general across unimanual and bimanual manipulation is not known. We investigated the generation of compensatory moments through hand placement and force modulation during bimanual manipulation of an object with variable center of mass. Participants were instructed to prevent object roll during the lift. Similar to unimanual grasping, we found modulation and covariation of hand forces and placement for successful performance. Thus this motor adaptation of the anticipatory control of compensatory moment is a general feature across unimanual and bimanual effectors. Our results highlight the involvement of high-level representation of manipulation goals and underscore a sensorimotor circuitry for anticipatory control through a continuum of force and placement modulation of object manipulation across a range of effectors.

NEW & NOTEWORTHY This is the first study, to our knowledge, to show that successful bimanual manipulation of objects with asymmetrical centers of mass is performed through the modulation and covariation of hand forces and placements to generate compensatory moments. Digit force-to-placement modulation is thus a general phenomenon across multiple effectors, such as the fingers of one hand, and both hands. This adds to our understanding of integrating low-level internal representations of object properties into high-level task representations.

Sensorimotor uncertainty modulates corticospinal excitability during skilled object manipulation

Sensorimotor memory built through previous hand-object interactions allows subjects to plan grasp forces. The memory-based mechanism is particularly effective when contact points on the object do not change across multiple manipulations, thus allowing subjects to generate the same forces in a feedforward fashion. However, allowing subjects to choose where to grasp an object causes trial-to-trial variability in fingertip positioning, suggesting a decreased ability to predict where the object will be grasped. In this scenario, subjects modulate forces on a trial-to-trial basis as a function of fingertip positioning. We suggested that this fingertip force-to-position modulation could be implemented by transforming feedback of digit placement into an accurate distribution of fingertip forces. Thus, decreasing certainty of fingertip position on an object would cause a shift from predominantly memory- to feedback-based force control mechanisms. To gain further insight into these sensorimotor transformation mechanisms, we asked subjects to grasp and lift an object with an asymmetrical center of mass while preventing it from tilting. To isolate the effect of digit placement uncertainty, we designed two experimental conditions that differed in terms of predictability of fingertip position but had similar average fingertip positioning and force distribution. We measured corticospinal excitability to probe possible changes in sensorimotor processing associated with digit placement uncertainty. We found a differential effect of sensorimotor uncertainty after but not before object contact. Our results suggest that sensorimotor integration is rapidly tuned after object contact based on different processing demands for memory versus feedback mechanisms underlying the control of manipulative forces. NEW & NOTEWORTHY The relative contribution of predictive and feedback mechanisms for scaling digit forces to position during dexterous manipulation depends on the predictability of where the object will be grasped. We found that corticospinal excitability shortly after contact was sensitive to digit position predictability. This supports the proposition that distinct sensorimotor integration processes are engaged, depending on the role of feedback about digit placement versus sensorimotor memory in controlling manipulative forces.

A new method based on quiet stance baseline is more effective in identifying freezing in Parkinson's disease

Freezing, an episodic movement breakdown that goes from disrupted gait patterns to complete arrest, is a disabling symptom in Parkinson’s disease. Several efforts have been made to objectively identify freezing episodes (FEs), although a standardized methodology to discriminate freezing from normal movement is lacking. Novel mathematical approaches that provide information in the temporal and frequency domains, such as the continuous wavelet transform, have demonstrated promising results detecting freezing, although still with limited effectiveness. We aimed to determine whether a computerized algorithm using the continuous wavelet transform based on baseline (i.e. no movement) rather than on amplitude decrease is more effective detecting freezing. Twenty-six individuals with Parkinson’s disease performed two trials of a repetitive stepping-in-place task while they were filmed by a video camera and tracked by a motion capture system. The number of FEs and their total duration were determined from a visual inspection of the videos and from three different computed algorithms. Differences in the number and total duration of the FEs between the video inspection and each of the three methods were obtained. The accuracy to identify the time of occurrence of a FE by each method was also calculated. A significant effect of Method was found for the number (p = 0.016) and total duration (p = 0.013) of the FEs, with the method based on baseline being the closest one to the values reported from the videos. Moreover, the same method was the most accurate in detecting the time of occurrence, and the one reaching the highest sensitivity (88.2%). Findings suggest that threshold detection methods based on baseline and movement amplitude decreases capture different characteristics of Parkinsonian gait, with the first one being more effective at detecting FEs. Moreover, robust approaches that consider both time and frequency characteristics are more sensitive in identifying freezing.

Neural Representations of Sensorimotor Memory- and Digit Position-Based Load Force Adjustments Before the Onset of Dexterous Object Manipulation

Anticipatory load forces for dexterous object manipulation in humans are modulated based on visual object property cues, sensorimotor memories of previous experiences with the object, and, when digit positioning varies from trial to trial, the integrating of this sensed variability with force modulation. Studies of the neural representations encoding these anticipatory mechanisms have not considered these mechanisms separately from each other or from feedback mechanisms emerging after lift onset. Here, representational similarity analyses of fMRI data were used to identify neural representations of sensorimotor memories and the sensing and integration of digit position. Cortical activity and movement kinematics were measured as 20 human subjects (11 women) minimized tilt of a symmetrically shaped object with a concealed asymmetric center of mass (CoM, left and right sided). This task required generating compensatory torques in opposite directions, which, without helpful visual CoM cues, relied primarily on sensorimotor memories of the same object and CoM. Digit position was constrained or unconstrained, the latter of which required modulating forces beyond what can be recalled from sensorimotor memories to compensate for digit position variability. Ventral premotor (PMv), somatosensory, and cerebellar lobule regions (CrusII, VIIIa) were sensitive to anticipatory behaviors that reflect sensorimotor memory content, as shown by larger voxel pattern differences for unmatched than matched CoM conditions. Cerebellar lobule I-IV, Broca area 44, and PMv showed greater voxel pattern differences for unconstrained than constrained grasping, which suggests their sensitivity to monitor the online coincidence of planned and actual digit positions and correct for a mismatch by force modulation.SIGNIFICANCE STATEMENT To pick up a water glass without slipping, tipping, or spilling requires anticipatory planning of fingertip load forces before the lift commences. This anticipation relies on object visual properties (e.g., mass/mass distribution), sensorimotor memories built from previous experiences (especially when object properties cannot be inferred visually), and online sensing of where the digits are positioned. There is limited understanding of how the brain represents each of these anticipatory mechanisms. We used fMRI measures of regional brain patterns and digit position kinematics before lift onset of an object with nonsalient visual cues specifically to isolate sensorimotor memories and integration of sensed digit position with force modulation. In doing so, we localized neural representations encoding these anticipatory mechanisms for dexterous object manipulation.

Motor Subtypes of Parkinson's Disease Can Be Identified by Frequency Component of Postural Stability

Parkinson’s disease (PD) can be divided into two subtypes based on clinical features—namely tremor dominant (TD) and postural instability and gait difficulty (PIGD). This categorization is important at the early stage of PD, since identifying the subtypes can help to predict the clinical progression of the disease. Accordingly, correctly diagnosing subtypes is critical in initiating appropriate early interventions and tracking the progression of the disease. However, as the disease progresses, it becomes increasingly difficult to further distinguish those attributes that are relevant to the subtypes. In this study, we investigated whether a method using the standing center of pressure (COP) time series data can separate two subtypes of PD by looking at the frequency component of COP (i.e., COP position and speed). Thirty-six participants diagnosed with PD were evaluated, with their bare feet on the force platform, and were instructed to stand upright with their arms by their sides for 20 s (with their eyes open and closed), which is consistent with the traditional COP measures. Fast Fourier transform (FFT) and wavelet transform (WT) were performed to distinguish between the motor subtypes using the COP measures. The TD group exhibited larger amplitudes at the frequency range of 3–7 Hz when compared to the PIGD group. Both the FFT and WT methods were able to differentiate the subtypes. COP time series information can be used to differentiate between the two motor subtypes of PD, using the frequency component of postural stability.

On the Role of Physical Interaction on Performance of Object Manipulation by Dyads

Human physical interactions can be intrapersonal, e.g., manipulating an object bimanually, or interpersonal, e.g., transporting an object with another person. In both cases, one or two agents are required to coordinate their limbs to attain the task goal. We investigated the physical coordination of two hands during an object-balancing task performed either bimanually by one agent or jointly by two agents. The task consisted of a series of static (holding) and dynamic (moving) phases, initiated by auditory cues. We found that task performance of dyads was not affected by different pairings of dominant and non-dominant hands. However, the spatial configuration of the two agents (side-by-side vs. face-to-face) appears to play an important role, such that dyads performed better side-by-side than face-to-face. Furthermore, we demonstrated that only individuals with worse solo performance can benefit from interpersonal coordination through physical couplings, whereas the better individuals do not. The present work extends ongoing investigations on human-human physical interactions by providing new insights about factors that influence dyadic performance. Our findings could potentially impact several areas, including robotic-assisted therapies, sensorimotor learning and human performance augmentation.

On neuromechanical approaches for the study of biological and robotic grasp and manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.

Role of digit placement control in sensorimotor transformations for dexterous manipulation

Dexterous manipulation relies on the ability to modulate grasp forces to variable digit position. However, the sensorimotor mechanisms underlying such critical ability are not well understood. The present study addressed whether digit force-to-position modulation relies entirely on feedback of digit placement and force, or on the integration of such feedback with motor commands responsible for digit positioning. In two experiments, we asked 25 subjects to estimate the index fingertip position relative to the thumb (perception test) or to grasp and lift an object with an asymmetrical mass distribution while preventing object roll (action test). Both tests were performed after subjects' digits were placed actively or passively at different distances (active and passive condition, respectively) and without visual feedback. Because motor commands for digit positioning would be integrated with position and force feedback in the active condition, we hypothesized this condition to be characterized by greater accuracy of digit position estimation and digit force-to-position modulation. Surprisingly, discrimination of digit position and force-to-position modulation was statistically indistinguishable in the active and passive conditions. We conclude that voluntary commands for digit positioning are not essential for accurate estimation of finger position or modulation of digit forces to variable digit position. Thus digit force-to-position modulation can be implemented by integrating sensory feedback of digit position and voluntary commands of digit force production following contact.NEW & NOTEWORTHY This study was designed to understand the sensorimotor mechanisms underlying digit force-to-position modulation required for manipulation. Surprisingly, estimation of relative digit position and force-to-position modulation was accurate regardless of whether the digits were passively or actively positioned. Therefore, accurate estimation of digit position does not require an efference copy of active digit positioning, and the hypothesized advantage of active over passive movement on estimation of end-point position appears to be task and effector dependent.

Communication and Inference of Intended Movement Direction during Human-Human Physical Interaction

Of particular interest to the neuroscience and robotics communities is the understanding of how two humans could physically collaborate to perform motor tasks such as holding a tool or moving it across locations. When two humans physically interact with each other, sensory consequences and motor outcomes are not entirely predictable as they also depend on the other agent’s actions. The sensory mechanisms involved in physical interactions are not well understood. The present study was designed (1) to quantify human–human physical interactions where one agent (“follower”) has to infer the intended or imagined—but not executed—direction of motion of another agent (“leader”) and (2) to reveal the underlying strategies used by the dyad. This study also aimed at verifying the extent to which visual feedback (VF) is necessary for communicating intended movement direction. We found that the control of leader on the relationship between force and motion was a critical factor in conveying his/her intended movement direction to the follower regardless of VF of the grasped handle or the arms. Interestingly, the dyad’s ability to communicate and infer movement direction with significant accuracy improved (>83%) after a relatively short amount of practice. These results indicate that the relationship between force and motion (interpreting as arm impedance modulation) may represent an important means for communicating intended movement direction between biological agents, as indicated by the modulation of this relationship to intended direction. Ongoing work is investigating the application of the present findings to optimize communication of high-level movement goals during physical interactions between biological and non-biological agents.

Towards Real-Time Detection of Freezing of Gait Using Wavelet Transform on Wireless Accelerometer Data

Injuries associated with fall incidences continue to pose a significant burden to persons with Parkinson’s disease (PD) both in terms of human suffering and economic loss. Freezing of gait (FOG), which is one of the symptoms of PD, is a common cause of falls in this population. Although a significant amount of work has been performed to characterize/detect FOG using both qualitative and quantitative methods, there remains paucity of data regarding real-time detection of FOG, such as the requirements for minimum sensor nodes, sensor placement locations, and appropriate sampling period and update time. Here, the continuous wavelet transform (CWT) is employed to define an index for correctly identifying FOG. Since the CWT method uses both time and frequency components of a waveform in comparison to other methods utilizing only the frequency component, we hypothesized that using this method could lead to a significant improvement in the accuracy of FOG detection. We tested the proposed index on the data of 10 PD patients who experience FOG. Two hundred and thirty seven (237) FOG events were identified by the physiotherapists. The results show that the index could discriminate FOG in the anterior–posterior axis better than other two axes, and is robust to the update time variability. These results suggest that real time detection of FOG may be realized by using CWT of a single shank sensor with window size of 2 s and update time of 1 s (82.1% and 77.1% for the sensitivity and specificity, respectively). Although implicated, future studies should examine the utility of this method in real-time detection of FOG.