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Sangwoo Park

Publications and source records attributed to Sangwoo Park.

95 records · Page 6Linked to original sources

On the Feasibility of Wearable Exotendon Networks for Whole-Hand Movement Patterns in Stroke Patients

Fully wearable hand rehabilitation and assistive devices could extend training and improve quality of life for patients affected by hand impairments. However, such devices must deliver meaningful manipulation capabilities in a small and lightweight package. In this context, this paper investigates the capability of single-actuator devices to assist whole-hand movement patterns through a network of exotendons. Our prototypes combine a single linear actuator (mounted on a forearm splint) with a network of exotendons (routed on the surface of a soft glove). We investigated two possible tendon network configurations: one that produces full finger extension (overcoming flexor spasticity), and one that combines proximal flexion with distal extension at each finger. In experiments with stroke survivors, we measured the force levels needed to overcome various levels of spasticity and open the hand for grasping using the first of these configurations, and qualitatively demonstrated the ability to execute fingertip grasps using the second. Our results support the feasibility of developing future wearable devices able to assist a range of manipulation tasks.

cs.RO↗

A Unifying Variational Perspective on Some Fundamental Information Theoretic Inequalities

This paper proposes a unifying variational approach for proving and extending some fundamental information theoretic inequalities. Fundamental information theory results such as maximization of differential entropy, minimization of Fisher information (Cramér-Rao inequality), worst additive noise lemma, entropy power inequality (EPI), and extremal entropy inequality (EEI) are interpreted as functional problems and proved within the framework of calculus of variations. Several applications and possible extensions of the proposed results are briefly mentioned.

cs.IT↗

An Alternative Proof of an Extremal Entropy Inequality

This paper first focuses on deriving an alternative approach for proving an extremal entropy inequality (EEI), originally presented in [11]. The proposed approach does not rely on the channel enhancement technique, and has the advantage that it yields an explicit description of the optimal solution as opposed to the implicit approach of [11]. Compared with the proofs in [11], the proposed alternative proof is also simpler, more direct, more information-theoretic, and has the additional advantage that it offers a new perspective for establishing novel as well as known challenging results such the capacity of the vector Gaussian broadcast channel, the lower bound of the achievable rate for distributed source coding with a single quadratic distortion constraint, and the secrecy capacity of the Gaussian wire-tap channel. The second part of this paper is devoted to some novel applications of the proposed mathematical results. The proposed mathematical techniques are further exploited to obtain a more simplified proof of the EEI without using the entropy power inequality (EPI), to build the optimal solution for a special class of broadcasting channels with private messages and to obtain a mutual information-based performance bound for the mean square-error of a linear Bayesian estimator of a Gaussian source embedded in an additive noise channel.

cs.IT↗

Gaussian Assumption: the Least Favorable but the Most Useful

This paper focuses on three contributions. First, a connection between the result, proposed by Stoica and Babu, and the recent information theoretic results, the worst additive noise lemma and the isoperimetric inequality for entropies, is illustrated. Second, information theoretic and estimation theoretic justifications for the fact that the Gaussian assumption leads to the largest Cramér-Rao lower bound (CRLB) is presented. Third, a slight extension of this result to the more general framework of correlated observations is shown.

cs.IT↗

On the equivalence between Stein and de Bruijn identities

This paper focuses on proving the equivalence between Stein's identity and de Bruijn's identity. Given some conditions, we prove that Stein's identity is equivalent to de Bruijn's identity. In addition, some extensions of de Bruijn's identity are presented. For arbitrary but fixed input and noise distributions, there exist relations between the first derivative of the differential entropy and the posterior mean. Moreover, the second derivative of the differential entropy is related to the Fisher information for arbitrary input and noise distributions. Several applications are presented to support the usefulness of the developed results in this paper.

cs.IT↗